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Citizen developers (sometimes referred to as “power users”) play a crucial role in bridging the gap between business requirements and IT capabilities. Despite lacking formal training in software development, these individuals drive innovation by building or customising solutions for themselves and their teams, streamlining repetitive processes, and enabling faster business transformations. Citizen developers are professionals who utilise no-code or low-code tools to address business needs without being formally employed as software developers or having a computer science degree. SlashData’s latest (Q3 2024) global survey reached nearly 10,000 respondents involved in technology projects*, either as professionals, hobbyists, or students. Of those, more than 7,000 were working as professionals, meaning that they earned their living working professionally in one or more of the areas defined in the footnote below. About 10% of these technology professionals met our criteria of being a citizen developer.     In this blog post, we explore what sets citizen developers apart from other technology professionals and the implications for the broader tech community. By understanding who they are and what motivates citizen developers, organisations can better leverage the strengths of this critical community to foster a culture of open collaboration in their organisations. Defining citizen developers To identify citizen developers through our survey, we excluded all technology professionals formally employed as software developers and those holding a university degree in computer science. We then filtered respondents who use at least some no-code/low-code tools in their workflow.  While improvements in AI and its coding assistance capabilities have empowered many non-developers to use programming languages and their respective tools, no-code/low-code tools remain the defining benchmark for citizen developers. Most technology professionals (51%) do not use no-code or low-code tools, but of the 49% that do, we compare them to citizen developers below. The distributions of the two groups are very similar, suggesting that no-code or low-code tools are not disproportionately valued or utilised in citizen developers' workflow vs other technology professionals.  Citizen developers’ experience in software development In the early career stages (less than 5 years of experience), citizen developers are disproportionally represented compared to traditional technology professionals. This suggests that non-software development professionals who are newer to the tech industry may gain interest early in their careers and may start getting involved with technologies to become power users. Conversely, at advanced experience levels (16+ years), citizen developers are less represented, indicating that they may transition into other roles or lack the lengthy career paths common among traditional tech professionals. Citizen developers are, on average, half a year earlier in their technology careers compared to other technology professionals. Citizen developers have an average of 3.5 years of experience, slightly less than the 4 years reported by other technology professionals. This raises the question: Do citizen developers aim to evolve into more technical roles?  Looking at their motivations for contributing to software development provides valuable insight into this question. Prevalence within startups Citizen developers are more common in startups, largely due to necessity. In lean organisations where resources are tight, such as startups, tasks requiring automation or technical solutions often fall to power users within the business.  We know from previous research that startups attract developers earlier in their careers . While, as noted above, this is due in part to necessity, it is also likely that citizen developers gravitate towards organisations where flexibility, experimentation, and rapid product iteration are the norm. These settings allow these professionals to transition into more advanced technical or leadership positions over time. In these dynamic environments, they may gain visibility and influence, leveraging their unique blend of domain expertise and technological aptitude to drive innovation. As we will see below, this mixed bag of skills can come in very handy when making technology purchasing decisions.  Citizen developers and tool purchasing decisions Citizen developers are notably active in influencing or making purchasing decisions for developer tools, often at a higher rate than their counterparts. A fifth of citizen developers (21%) approve expenses compared to just 14% of their colleagues. Likewise, 30% of citizen developers are responsible for specifications, compared to 24% of other technology professionals. However, when it comes to purchasing for individual use, citizen developers trail their counterparts.  Citizen developers are more likely to be involved in purchasing decisions than other technology professionals. The high degree of involvement by citizen developers in company-level purchasing decisions may seem counterintuitive, given their slightly earlier career stages. However, their involvement reflects their hands-on, practical approach to addressing workflow needs and their understanding of business needs. These power users understand the business side and are involved with the technical side to a degree that allows them to serve as a bridge between technical and business stakeholders.  Are citizen developers part of your target audience? Let’s dive into their preferences together. Contact us.  About the author Brayton Noll is a behavioral scientist with a background in climate change and environmental research. He holds a PhD from TU Delft in computational social science, with his thesis focusing on human behavioral dynamics and climate adaptation. He has five years of experience working with data analytics. * By “technology projects” in this report, we mean any of the following types of software development projects: Web apps / Software as a Service, mobile apps , desktop apps , backend services,   augmented reality (incl. mixed reality) ,  virtual reality, games, data science, machine learning / AI, industrial IoT, consumer electronics devices / consumer IoT,   apps/extensions for third-party platforms and ecosystems, or embedded software.

In a world that’s changing faster than ever, businesses face an increasingly complex environment. Emerging technologies, such as artificial intelligence, are transforming industries. At the same time, shifting consumer behaviours, political changes, and economic disruptions create additional challenges and opportunities for businesses. Amid this complexity, market research becomes an essential tool for building successful business strategies, offering the insights needed to adapt, innovate, and thrive. In this blog post, we'll explore the top five reasons why market research should be a cornerstone of your business planning for 2025, helping you make data-driven decisions that address future challenges and opportunities. Understand the market and identify trends To succeed in today’s rapidly changing market, businesses must keep up with market dynamics and emerging trends. Market research plays a pivotal role by helping companies identify critical success factors and anticipate shifts, enabling strategic and informed decision-making. By closely monitoring elements such as industry trends, innovations, regulatory changes, and consumer behaviours, businesses can adapt proactively and maintain their competitive edge. Market research can also help uncover untapped growth opportunities, enabling businesses to expand strategically. By identifying prospects such as geographic expansion, targeting underserved niches, or innovating with new products and services, businesses can make informed investment decisions that drive growth. An essential process for identifying and evaluating these opportunities is Total Addressable Market (TAM) sizing, which evaluates the number of potential customers/users and potential revenues. Understanding the TAM allows businesses to determine the viability of pursuing specific markets and guides the level of investment required to capitalise on these opportunities. Leveraging them not only opens new revenue streams but could also enhance a company's competitive position. Competitive intelligence equips organisations to stand out, differentiate, and strategically position themselves for long-term success. Additionally, market research provides a comprehensive understanding of the competitive landscape. By analysing competitors’ strengths and weaknesses, businesses can identify areas to focus on, such as enhancing customer experience, refining product offerings, or optimising marketing strategies. This competitive intelligence equips organisations to stand out, differentiate, and strategically position themselves for long-term success. Know your customers The better you know your customers, the less you need to guess. Understanding your audience is key to serving their needs. Market research allows you to uncover not only the explicit needs of your customers but also their unmet needs and pain points. By diving deep into consumer insights, businesses can tailor their offerings to provide more value. For example, a software company may discover that its target users seek better integration with specific tools. By prioritising seamless integrations and actively promoting these features, the company can enhance customer satisfaction and retention while also attracting new customers who value these capabilities. Additionally, differentiating customer personas allows businesses to design targeted plans that cater to the unique characteristics of each segment. Market research can aid in identifying distinct personas based on behavioural, attitudinal, demographic, and psychographic data, guiding how to reach and engage them effectively. For instance, from our extensive research experience, we commonly see how regional differences are crucial in shaping customer behaviour and preferences. Understanding these regional distinctions helps businesses develop localised strategies , ensuring products, marketing, and services resonate with specific audiences. Identify and mitigate risks Every business decision carries inherent risks that, if ignored, can result in significant setbacks. Market research is essential for identifying these risks early, enabling businesses to plan effective mitigation strategies and adapt proactively rather than reactively, which can often be too late. Know the risks, plan for them, and sleep better at night. A prime example of market research’s value is its ability to minimise the risk of launching an unsuccessful product. Through concept testing, surveys, focus groups, and user testing, businesses can gauge consumer reactions and refine their offerings before committing substantial resources. This approach ensures the final product meets customer needs while significantly reducing the chance of failure. For example, early-stage concept testing allows businesses to understand customer preferences and refine their offerings accordingly. By employing techniques such as MaxDiff surveys, conjoint analysis, and monadic testing, companies can compare various concepts and pinpoint the attributes that truly resonate with their target audience. With these insights in hand, organisations can iteratively develop solutions that align with market demands, increasing the likelihood of a successful product launch and accelerating the path to product-market fit. Improve products and services Analyse, optimise, repeat. Good products are never truly finished. Market research can also be a powerful tool for refining and optimising products and services , informing product roadmaps to better align with market demands. By collecting insights from customers (or even competitors’ customers), businesses can identify areas for improvement, such as enhancing technical support, adding new features, or addressing existing pain points. An essential part of this process involves using quantitative methods like MaxDiff and conjoint analysis to determine the most appealing combination of features, understand the relative importance of product attributes, and optimise the feature and price mix for new products. Making this an iterative process ensures that products and services evolve alongside customer needs and industry trends, boosting customer satisfaction, increasing retention rates, and expanding market share. A critical aspect of product optimisation is crafting an effective pricing strategy. A well-designed pricing approach not only generates revenue but also ensures positive cash flow, which is essential for funding strategic initiatives and growth. This is particularly important in industries like tech, where companies often face challenges converting free users into paying customers. Market research sheds light on the motivations, pain points, and preferred pricing models that influence customers’ decisions to upgrade.  Moreover, techniques such as the Van Westendorp price sensitivity meter and the Gabor-Granger method can be employed to understand consumer price sensitivity more effectively. With these insights, businesses can simplify the transition from free to paid , maximising conversions while enhancing the customer experience. But pricing optimisation doesn’t stop there. Market research also helps businesses understand consumer price sensitivity and competitor pricing strategies. This enables companies to establish optimal price points and create tiered offerings that not only attract and retain paying customers but also deliver exceptional value. Strengthen brand strategy A strong brand is the foundation of a successful business, and market research plays a pivotal role in crafting branding strategies. By measuring and tracking the strength of your brand  and your main competitors, you can understand how your brand is perceived in the market. This includes key metrics such as awareness, loyalty, perception, and positioning, which are critical for assessing the health of your brand. You can’t improve what you don’t measure. By doing market research, companies can inform their brand strategy plans, allowing them to adjust their messaging and positioning in response to shifts in consumer sentiment. Understanding how your audience feels about your company or offerings enables you to make strategic decisions that enhance brand perception and deepen customer loyalty. This could mean pivoting your messaging, highlighting different brand values, or finding ways to differentiate more effectively. Additionally, market research can uncover areas of opportunity to strengthen the brand's connection with the audience. Whether refining the brand’s story, tapping into new channels to reach customers, or adjusting the visual identity to stay relevant, these insights ensure that brands evolve in line with consumer expectations and remain resilient against competitors. At SlashData, we specialise in delivering actionable, data-driven insights tailored to your unique business challenges. Whether you’re exploring new markets, refining your brand strategy, prioritising product features, or honing your product roadmap, our expert guidance will help you elevate your strategic planning. Contact us today ! About the author Álvaro is a market research analyst with a background in strategy and operations consulting. He holds a Master’s in Business Management and believes in the power of data-driven decision-making. Álvaro is passionate about helping businesses tackle complex strategic business challenges and make strategic decisions that are backed by thorough research and analysis.

In the expansive universe of software developer tools, where both free and paid choices abound, vendors strive to carve out a niche and capture the attention of developers. This blog post provides a glimpse into our recently published Pricing Strategies for Developer Tools report , which explores what motivates developers to adopt new tools, the factors they consider when they evaluate them, and the pricing models that best align with their needs. Here, we provide a practical guide that can help you tailor your offering to capture the attention of developers and gain a competitive edge in the market. Inside the developers’ mind: Understanding tool adoption and evaluation factors To set the stage, it’s crucial to understand the primary motivation driving developers to adopt tools. Our research found that the majority (56%) of developers prioritise increasing productivity, with improvements in code quality (13%) and performance (7%) trailing far behind as secondary priorities. All other goals are prioritised by 5% or fewer developers. Therefore, tailoring your offering and communication to emphasise how your service enhances productivity can effectively capture developers’ attention. When delving into the factors developers weigh when assessing a new offering, feature availability takes the lead, influencing the decisions of 31% of developers, closely followed by the importance of high-quality documentation (25%). Additionally, 23% and 18% of developers emphasise the value of free plans and free trials, respectively. Therefore, providing a free plan or trial becomes paramount for developers to test and determine whether a tool aligns with their requirements. Without this option, your service may be easily overlooked, prompting developers to explore competing offerings. Moreover, over one in five developers (21%) considers transparent pricing an important factor during tool evaluation. Hence, hiding pricing structures behind contact forms or sales calls poses the risk of losing potential users. Pricing should be straightforward, ensuring expense predictability and avoiding hidden costs or fees. However, it should be noted that the importance of transparent pricing drops to 14% among developers in large organisations (1,000+ employees), as enterprise plans often require direct engagement with sales for tailored quotes. Navigating the fine line: Ensuring competitiveness without overextending free offerings Offering a free plan or trial for developer tools is essential, but simply onboarding developers to these free offerings may not be enough. Developers often abandon free plans and trials due to limitations in features, functionality, and usage limits. Approximately one-third of developers who abandoned a free plan or trial in the past year cited these reasons. On the flip side, the primary motivations for developers to upgrade from a free to a paid plan include gaining access to advanced features and having higher or no usage limits. 44% of developers upgraded to get access to advanced features, and 31% to increase usage limits. Hence, when designing your free offerings, it is crucial to achieve a delicate balance. Avoid making your free plan uncompetitive, yet be cautious not to offer excessive functionality for free. Feature availability, as emphasised in the previous section, is the most important consideration for developers when exploring new platforms. A non-competitive free plan might lead developers to abandon your product, seeking alternatives or overlooking your tool altogether. Conversely, providing too much functionality for free may attract numerous developers to your free plan, but converting these free users into paying customers becomes challenging if they already have access to all the necessary functionality without upgrading. Therefore, finding the right equilibrium is key to a successful pricing strategy. To achieve this balance, it’s essential to first map out the offerings of your main competitors and strategically design your pricing strategy in light of this information. For any assistance during this research phase, please feel free to reach out. Pricing perspectives: How do developers prefer to pay for tools? When asking developers about the key pricing  factors influencing their choice to upgrade to a paid version of a developer tool, one factor emerges as the clear frontrunner: the pricing model / fee structure, considered by nearly half of developers when upgrading (49%). Other important considerations include the vendor’s reputation and trustworthiness, the total cost of ownership, and suitable pricing tiers, each considered by approximately a third of developers. Taking a closer look at the most important pricing factor (the pricing model), we found that subscription-based pricing holds a substantial lead as the preferred option for developers, with 53% expressing a preference for it. In contrast, one-time purchases (39%), usage-based pricing (34%), per-seat licensing (21%), and pay-per-feature (13%) models lag behind. However, preferences in pricing models can vary depending on the type of tool. For example, 53% of developers favour usage-based models for cloud services, while 44% prefer a one-time purchase for integrated development environments (IDEs) or text editors. Hence, aligning your pricing model with developers’ preferences for your offering type is crucial. Digging deeper into subscription-based models, specifically into billing preferences, monthly and annual billing cycles emerge as the top choices. Monthly billing is favoured by 43% of developers, compared to 35% who prefer annual billing. To cater to the majority of developers, it is essential to offer both options. Interestingly, we found in our analysis that business size influences billing preferences. For instance, developers in small businesses (2 - 50 employees) show a higher inclination towards annual billing (43%) compared to those in larger companies (around 33%). This inclination is likely driven by the cost savings associated with annual plans, aligning with the financial constraints often faced by smaller companies. On the other hand, enterprise developers show a greater preference for quarterly plans (14%) than their counterparts in smaller companies (5%). This could be attributed to the intricacies of budgeting and financial planning processes in larger enterprises, typically structured on a quarterly basis. If targeting enterprises, incorporating quarterly billing alongside monthly and annual options can set your offering apart. Moreover, this flexibility could help overcome potential obstacles tied to departmental approvals, particularly in finance - a recurring challenge identified in the upgrade process to enterprise plans, as we cover in the full pricing strategies report. While this blog post offers a sneak peek into the intricate world of developer tool pricing, our journey into the minds of developers is far from over. For a more thorough understanding, we invite you to explore our Pricing Strategies for Developer Tools report . Uncover a wealth of additional data that delves beyond the surface, empowering you to refine your pricing strategy with precision. This report includes detailed analyses, full distributions of factors, breakdowns by variables such as company size, roles, and decision-making power, and other information that surpasses the scope of this blog post. Are you helping developers with your offering? Get in touch and we can look together at developers' needs.

SlashData recently published a ground-breaking white paper addressing the Holy Grail of questions among Developer Relations, community managers, Developer Program Managers and more. The Developer Engagement Value framework calculates the added value every onboarded developer brings in real dollars. This is the total value that a developer is expected to bring over a period of time either by using a vendor’s technologies themselves (direct value) or by inducing/supporting others to do so (indirect value). In this blog post, we are diving deeper into the practical use of the framework by showcasing a real-data example of a cloud vendor and how we calculated the value of their developer community across all their products and services for four different segments. Hop on directly to the full white paper. The use case of a cloud vendor We considered a – hypothetical – scenario where the cloud vendor wants to estimate the value of their developer community across all their products and services and is interested in doing so for four journey-related segments: students, junior developers, specialists / senior developers (specialists for short), and managers. Using real data , we demonstrated how you can use the Developer Engagement Value framework to: understand developer segment transitions, prioritise audiences for outreach, select the value-maximising initiatives for these segments, and understand how to optimise your offerings. Here are some of our key findings: 68% of student developers onboarded by the cloud vendor will be professionals with some tooling decision-making influence within their organisation within a year . This implies that any investments the cloud vendor makes in students will begin to bear (more) fruit in – up to – a year later in 68% of the cases. Senior developers and specialists are the most valuable segment out of the four we considered (students, junior developers, specialists / senior developers, and managers), each developer in this group bringing $15, that is 2.3 times more than the dummy ARPU we assumed. This speaks volumes as to why ARPU is not sufficient to capture the full value that a developer brings , and why you should therefore be adopting a full-view lifetime value instead. In particular, specialists bring slightly more value than the managers , and that stems from higher Support and Skill-Builder value ($4.22 vs $3.73) and higher Developer Feedback Value ($8.53 vs $8.00). Different DevRel activities are expected to boost value of different types for any given segment . More specifically, we found that among the cloud vendor’s junior developers, those who value training courses and hands-on labs are 17% more likely than those who don’t to bring usage-inducing value. These initiatives, however, seem to have only a small effect on the product-enhancing value of junior developers. Therefore, focusing on these will mostly have an impact on the usage-inducing value.  On the contrary, those among junior developers who consider documentation and sample code to be important bring 15% more product-enhancing value than those who don’t , whilst, the effect of good documentation on usage-inducing value is only 2% higher for those who consider it important vs those who don’t. Therefore, If the focus is to increase junior developer contribution and feedback, focusing on good documentation is a good strategy, as it will attract junior developers who are more valuable that way. There is more to this story and you can read it all in the full white paper .  #developerdollarvalue #developervalue #cloud #dev #developervaluemodel #developervalueframework

Yes. You read the title right. An answer to the worst nightmare of industry professionals in developer-facing roles. This includes people in Developer Relations, community managers, Developer Program Managers and more! It’s not just us saying it; it’s the people in these roles who have expressed how challenging it is to prove the value an onboarded developer brings, and they have done so in podcasts , panels and 1 to 1 discussions we had. That’s why at SlashData, we developed the framework that calculates the added value every onboarded developer brings in real dollars. In our thought leadership report, we show you how to calculate this dollar value by introducing the concept of Developer Engagement Value . The total value that a developer is expected to bring over a period of time either by using a vendor’s technologies themselves (direct value) or by inducing/supporting others to do so (indirect value). It is a forward-looking metric that takes into account the variable nature of developer behaviour and introduces a framework to calculate developer value in real dollars. You can access the full framework here . Or read on for more information.  Why do you need to know the value an onboarded developer brings? Developers are more than mere product or service users. Developers are unarguably partners and co-creators who add value that extends well beyond the direct revenue stemming from technology usage. Many Developer Relations (DevRel) and developer marketing practitioners struggle to prove just how valuable an onboarded developer is, and, consequently, to justify their budget investments in DevRel. Even if they do get their budgets approved, they are faced with the problem of how to optimally allocate this budget to the different activities. But are DevRel budgets the only reason why you would need to estimate the value that a developer brings? How about when launching a new developer product? Won’t you need a way to predict how many developers this new product will attract and how much value these new developers will bring? For decades, Customer Lifetime Value (CLV or LTV) has been used to predict the value a client will bring throughout their ‘lifetime’ (length of relationship) with a company. Model setup and estimation was fairly straightforward at the time when all we had to worry about was direct revenue and transactional data. But in the developer ecosystem and in the era of network effects, indirect revenue, influencers, open source, and developer communities of all shapes and sizes… how do you capture value? This is what we are after with the Developer Engagement Value . 4 key questions to answer first Estimating the value that a developer brings is a daunting task, given the indirect value contributions and network effects intrinsic to the developer ecosystem. Challenges, however, begin a lot earlier in the problem definition process than the indirect value estimation stage. Considering these four key questions will help us to define the boundaries of the problem better: Whose value should you estimate? As discussed earlier, it’s not just those using your products. We posed this question also to our community of DevRel practitioners, and we got back a broad spectrum of answers. See the full report for a selected set of their responses. Can you observe the developer journey? Time is a continuum and observing a developer’s journey uninterrupted in this continuum is one of the most challenging endeavours. Telemetry alone will not get you there. How should you define ‘lifetime’? What is the time horizon for your predictions? How far into the future should you try to see and estimate value for? Do you really need a dollar value estimate per onboarded developer? It depends on what your end goal is. For example, if what you’re trying to achieve is optimal prioritisation of DevRel initiatives, then a relative, rather than an absolute, value will suffice. If, however, you need a number for your ROI and budget calculations, then you do need a dollar value estimated. The DEV framework As we mentioned earlier, the concept of Customer Engagement Value (CEV) has been around for more than a decade. We built on the model proposed by Kumar et al. (2010), adjusting and extending it to capture all the forms of engagement that are typical to developers. In a nutshell: Our framework proposes a method of estimating the total value that a developer is expected to bring over a period of time, either by using your technologies themselves (direct value) or by inducing/supporting others to do so (indirect value). We call this the Developer Engagement Value (DEV) , and it is a forward-looking metric that takes into account the variable nature of developer behaviour. To arrive at the Developer Engagement Value, SlashData identifies seven key areas from where developer value stems – seven value categories: Developer Direct Value (DDV) Supporter and Skill-builder Value (SSB) Peer Influencer Value (PIV) Decision-maker Influencer Value (DmIV) Developer Referral Value (DRV) Developer Feedback Value (DFV) Developer Contributor Value (DCV) Then, factoring in data from its global developer surveys, SlashData can map all the evolution paths that the developer segments of interest can theoretically take in the course of a selected forecasting period. The next step is to  build models to find the link between developer value and specific initiatives (DevRel, developer marketing, pricing strategy, or product feature design) and finally provide scenarios which show you how each initiative is expected to change the value of each segment.  The framework is fully flexible as it can be applied to a single product, to a group of products or across your whole business. It is also sensitive enough to pick up nuances between similar initiatives and, as such, can provide you with granular insight on specific activities. What can the Developer Engagement Value framework do for you? How are you planning to use it? Dive in the full version and here’s to a brighter future. Download the framework . #developercommunity #developerdollarvalue #developervalue #roi

In the blog post, Take your Data to Dinner , we discussed the importance of clean online survey data: not all survey responses are suitable for analysis – in fact, negative and often fraudulent actors abound. That blog explained how to screen data in order to establish its reliability and cleanliness. In this post, the focus is more technical. Looking strategically at what modern, industry-leading data collection methodology should look like, we unpack the nuts and bolts of the kind of information a market research firm should be collecting from their survey respondents so as to be informed about their quality of the data they provide. What counts as a fraudulent response to our surveys First and foremost, who are the negative actors that we’re talking about here? Before jumping in, it should be noted that these groups are not the only creators of dirty data. At SlashData, we have observed three categories of fraudulent respondents, broadly speaking:  Complete response bots. These bots circumnavigate a survey tool and deliver their answers as a complete set directly to the end point of an API. Think of it as a fully packaged response delivered without even a click needed on the survey tool. Their responses feel forced, clumsy, and lack the human signature. Bot responses from web automation tools. It is always sad to see sophisticated web debug tools such as Selenium harnessed in this manner. These web automation tools work by taking control of the browser according to a programmed routine designed by a developer. It may not be wholly surprising that for a market research firm in the tech space (with a proud pedigree amongst the developer audience) we have seen a goodly few iterations of this sort of bot. Responses like these have hidden systematic patterns which can lead to their detection. Humans working as click farms. This is an individual or a group utilising one or more physically or even virtually different devices in order to register multiple responses to a survey. These responses provide human-like responses but often reek of disinterest and are usually filled with contradiction. Their answers exude artificial resonance.  I’ll explain how we tackle each of these groups. As a prerequisite, I’ll explain the information SlashData gathers so as to do this. Thereafter the overall mechanism, a trust index, which integrates the multiple information sources. Equipped with this, I’ll return to each of these negative actor groups explaining each trip themselves into negative trust territory. A decision is only as good as the information up which it is made. Judging data quality on a number of unique information pieces Before making any decision, it is obviously prudent to gather information. The nightmare situation of any court judge (or market research firm) is the presentation of new evidence mid-trial: not only does it prompt re-evaluating all that has gone before but, in some instances, it casts doubt on the information already provided. For some market research firms, the threat that new ‘mid-trial’ information poses is so concerning that it acts as a deterrent from even seeking such information in the first place. This is a research bias! It is a bias that helps explain why market research firms say that they already have enough information to decide the quality of a respondent and are not hungry for more or to be challenged.  To avoid dismissing information with an important impact on our understanding of the cleanliness of our data, we do not accept this position at SlashData. Instead, we have focused on acquiring several unique pieces of information in order to generate an overall mechanism – a trust index – which integrates the information we are able to gather about our respondents into a single score against which we are able to evaluate their credibility as a bona fide respondent. It is obviously only worth designing a trust index if you have multiple sources of information such as click position monitoring, reCaptcha validation, IP and proxy detection methods; and this is just to name a few. Some of the key pieces of data that are core to SlashData’s approach in data collection standards are the viewpoint data (telling us exactly how much of the question the respondent engaged with), per-question timing, and third-party validation mechanisms such as GitHub verification for developer profiles. Constructing a trust index for our data Just having information does not give an answer. That is why constructing a trust index is such a sophisticated (and yet essential) process.  Here, The Trust Index designed at SlashData, is the key to a coherent system of quality control which works by tracking actions that build and diminish trust. To give an example, a response that does not use privacy persevering tools and is of the same geolocation and reported location builds trust. Similarly, a response that uses privacy preserving tools is trust neutral – it could be either a good or bad actor and based on this information alone, there is no sufficient evidence to determine either way. But couple privacy preserving tools with a signature that suggests it is the same device, close starting times and known incentives to defraud — a picture of overall trust diminishment occurs.  Deploy and Detect Let us return to the three groups of negative actors we identified above to demonstrate how we are able to detect each by deploying our industry-leading data collection methodology. Complete response bots. This type of bot scores very negatively on the Trust Index by bypassing many of our other data collection mechanisms – for instance, they would not have a sensibly defined viewpoint (because their responses did not come through a survey tool). This is a quick and reliable red flag to their credibility which means that we can be completely sure that this type of bot has been completely removed from our clean data at SlashData. Bot responses from web automation tools. This is a more sophisticated type of bot fraud. Because the bot interacts with the survey tool, it is able to create responses that contain basic viewpoint information and other artefacts that our other mechanisms of data collection are on the lookout for. There are some dead give-aways, though: the bots’ response times between questions are either fixed (taking precisely 2 seconds for instance) or follow some type of probability distribution, such as being normally or uniformly distributed. A real human response would take more or less time per question depending on the length of the question, the sophistication of the question (grid or list) and if the question is multi- or single-choice. Too much uniformity in this area signals a response of low trust value. Web automation tools also fail to pass reCaptcha tests. A failure of a reCaptcha test in any instance is an extremely trust diminishing action .  Humans working as click farms. This type of fraud requires screening through multiple different data sources in order to be detected since it is a broad group within which are several levels of professionalism. The least sophisticated examples answer questions carelessly, almost randomly and thereby fail multiple trust tests for consistency; those that are slightly more sophisticated may attempt to change devices or use privacy preserving tools, but subtle pointers  give them away and they are inevitably detected. The most sophisticated require the analysis of multiple patterns/combinations involving unlikely userAgent device signatures, privacy information and responses.  You cannot prevent, fight or detect fraud if you do not have the data.  Do not let cancerous data consume your research. The importance of partnering with a market research firm which is constantly committed to the improvement of data collection methodologies for online surveys is one way you can avoid publishing noise and instead focus on making a noise about your research! We can get the clean data you need to optimise your strategy. How? Let’s talk . About the author Jed Stephens, Senior Data Scientist Jed has several years of research experience in the academic and industry sectors, mainly focusing on applied statistical research and computational implementations of new statistical methods. He holds an MSc in Statistics. His interest is in turning data into informed, actionable decisions.

What do developers expect from tech leaders in their developer program offerings? How do the leading developer programs compare? If you are looking for answers to these questions, then the Developer Program Benchmarking is for you.  What is the Developer Programs Benchmarking? It is SlashData's semi-annual market analysis on engagement and developer satisfaction, of industry-leading developer programs. Working with developers is challenging and modern developer programs consist of myriad activities including: Documentation Providing sample code Developer education Tooling In-person events Online communication among others.  It is hard to be great at everything, and it is hard to allocate effort and money effectively for maximum impact. So, we benchmark the developer programs against each other and in doing so, we provide a clear path to improving your own developer program.  What can the Developer Programs Benchmarking help you improve? There are two main areas in this benchmarking study that can help you improve.  First, measure what developers value in various resources and activities, in all their diversity, across several segments of the developer population.  Second, we highlight the best-practice leaders and what makes them stand out. There is no single leader across all 22 activities we measure —everyone can improve somewhere.  To understand the success of the various developer programs included in our research, we use three key metrics:  Adoption —the percentage of developers in our survey that use each program. Engagement —how frequently the users of each program consume its resources. Satisfaction —how developers score each attribute of the programs they use, equal to the proportion of five-star reviews minus the proportion of one-and two-star reviews What new insights are there from the leading developer programs in Q3 2023? The main highlight? Many smaller vendors eclipse the established market leaders' satisfaction scores Developers' answers in public forums In each new edition, we have a special "Deep Dive" where, on top of the main insights on Developer Programs, we focus and shed light on a more specific area of Developer programs. For this edition, we added a Deep Dive on Answers in public forums. Here are the questions we answer. Which types of developers value answers in public forums the most? How often do developers ask questions, answer questions, or otherwise utilise public forums? What are the most important characteristics of a useful answer in a public forum, and how does this change by developers’ experience levels? How satisfied are developers with the quality, frequency, and speed of vendors’ responses to questions in public forums? You can find more details about developers’ preferences for developer programs at the dedicated Developer Program Benchmarking page . If you are looking to benchmark your developer program against the leaders, please get in touch .

Clean data is difficult to define. Simply, clean data is data that is analysis ready, but the term ‘analysis ready’ has baked into it much more than initially meets the eye. Perhaps then, the easiest way to get clear on what clean data is, is to understand what clean data is not. After all, as Tolstoy put it, “ All happy families are alike; each unhappy family is unhappy in its own way .”  Dealing with dirty data Dirty data is, by definition, data that is not analysis-ready - it is fraudulent, corrupted, or distorted in one or several of a number of ways, depending on how the data is provided. In surveys, for example, questions can be hurriedly answered, answered by selecting at random, answered systematically randomly, such as by always selecting the third option, answered in pretence, answered boastingly, and so on and so on. And this is just to name a few.  Suddenly, the data is corrupted, and what we are left with is not fit for clean, reliable analysis. Let alone decision-making.  What this means in practice is that it is only the data from respondents who are genuine and also consciously engaged (with a survey) that should be considered “clean”. Clearly a market research firm needs to be able to provide the process of screening for the various forms of dirty data. Clean data are necessary for real-world, tangible decisions A simple equivalent might be something like this. Imagine that you’re a user on an online dating platform. You’re looking to find your match, but out there online, it’s tricky - how do you know the people you meet are who they say they are? What if they’re only funny over text? What if, in reality, they don’t look like their profile picture? What if their online persona is only just that? Meeting someone in person gives you an immediate sense of whether that person is genuine or not — but online, we become reliant on cues: does my match eat the same types of food as me, watch the same shows, or support the same causes? These are all proxies for that first meeting when your instinct takes over and screens your match. That first meeting is the dirty data detection mechanism of dating. In an online survey, we almost never meet our participants in person. Getting to clean data, therefore requires building mechanisms to screen your ‘matches’ in the same way as you might in the online dating world. Without the proper infrastructure, one is liable to allow in those who are non-genuine.  At this point, you’ve scrolled through your potential matches online, and now it’s time to get serious. You want to begin a conversation, get to know them better, and check that when you actually talk to them, they are who they say they are. Being a researcher myself, I would suggest something scientifically proven to achieve results, such as Arthur Aron’s 36 questions which lead to love . This is also why all our clients benefit from survey questions written by our experienced market research analysts. Without a well-written question, the answer will always appear as if it was dirty data. Surveying and producing data beyond the ‘what’, looking at the ‘how’ We all know that on a date, the ‘how’ the question is answered is as important as the ‘what’ was answered. Enter SlashData’s bespoke survey tool. Whilst the survey is asking questions written by our experienced market research analysts, the survey tool gathers information about how respondents are answering the questions in order to screen for potentially non-genuine ‘matches’. It is this “how” that is critical to our advanced integrated cleansing system. Clean data example 1 Here is a concrete example: when speaking to other researchers, they are often shocked to know that at SlashData, we know exactly how long it took a respondent to answer any given question. The industry standard screen is ‘total time in the survey,’ but this is easily exploitable by respondents. How genuine do you think your date would be, for example, if they spent ten minutes answering your first question about the other dates they had met online but only 10 seconds answering all your other questions about likes, dislikes, family, work, hobbies, hopes and dreams? Their total survey time might be 10 minutes and 30 seconds, yielding a respectable 2min, 37 seconds per question average (over four questions), which, by industry standards, would yield an acceptable ‘total survey time’. Industry standards would tell you your match is ‘clean’, but you’d be right in feeling more than a little dubious.  At SlashData, we would be looking far closer at the time taken to answer each question because, when you’re looking for ‘the one’, it matters. This innovation would not be possible without our survey tool. Clean data example 2 Another example: as your date progresses and you start to learn more it is only human nature to complete a consistency check. Think of it as checking your respondent’s life story. “You’ve made a React app? But you told me you didn’t know JavaScript”. A red flag. A little later, you realise your first date is actually a UI designer. Consistency rules are critical to detecting if the picture the respondent paints stacks up as a whole. For every three questions SlashData typically implements a consistency rule - a large survey may consist of sixty plus validations. These rules allow us to check whether the data we’re getting is reliable. While these rules can be implemented regardless of the survey tool, you should be enquiring if your market research firm takes care to consider and implement these.  Data consistency is key A flip side to consistency is advanced pattern detection. Is your date taking the same to consider each of your questions or are they disinterestedly answering via the easy way out? At SlashData, we’ve seen respondents who have been recruited from top panel providers who nevertheless always choose the third option on the list. Depending on the survey tool your market research company used this may be impossible to detect if the options are randomised - how do you know whether your respondent has scrolled down enough on the screen to grasp the full question, or whether they’re simply picking from options that they can immediately see? These characteristics are critical to know when deciding how trustworthy a respondent is.  After all this, imagine the worst case scenario. Imagine after effort - all that swiping and small talk and screening out the dodgy ones -  you turn up to find that your date is…just here for the food. You’ve been let down and probably feel used. This is an instance where the incentives (a nice meal or cash amount for answering the survey) yield problematic results. In an online environment, it requires industry-leading adaptations to detect repeat responding and bot responses. An advanced cleansing methodology should take into account the device used to answer the survey, whether any proxy, VPN, or IP masking was used — all while not penalising legitimate use of these privacy tools. This requires the complex consideration of response patterns and respondent metadata. Bot and repeat responders are a real problem for clean data — both artificially inflate the number of survey responses as well as add considerable noise to the results. Consistency checks also form an important aspect of checking for this type of response data. Love is a serious matter. Clean data is crucial. Finding a genuine match takes effort. All are as true for screening online data as they are for online dates. To find that the data is ‘analysis ready’ requires a number of mechanisms to sift out a myriad of dodgy dates or dirty data that shouldn’t be underestimated in their importance. Per question speed tests, click pattern detection, consistency checks, AI bot detection, repeat responder detection are just some of the technical achievements of SlashData’s cleansing methodology. SlashData’s bespoke in-house survey tool is best in class in providing these inputs to any cleansing process. Is your data clean? It is critical to ask your market research partner if they have the information to actually ensure this is achieved. If you want to better understand our process or explore a specific topic together, let’s talk . About the author Jed Stephens, Senior Data Scientist Jed has several years of research experience in the academic and industry sectors, mainly focusing on applied statistical research and computational implementations of new statistical methods. He holds an MSc in Statistics. His interest is in turning data into informed, actionable decisions.

Nowadays, developers have an abundance of options to choose from when it comes to finding information about software development and staying up-to-date. Nevertheless, their needs and preferences vary  depending on where they stand on their developer journey and based on a few key characteristics. If you would like to understand what those are and how they affect developer information choices, then keep reading! In this blog post, we draw data and insights from SlashData's 27th Developer Nation survey, which was fielded in Q3 2024 and reached 9k+ developers worldwide. Open source communities and social media are the leading resources where developers go to find information Open source communities (43%) and social media (41%) are the leading resources for developers globally to gather information  and stay up-to-date about software development, according to our data. In comparison, only 3% of developers rely on vendor-organised events, while other resources, such as meetups and hackathons, also see limited (c. 14%) interest among developers. Vendor-driven resources including official websites, newsletters and/or events, are used by ~40% of developers. Experience is a key factor affecting information resources preferences Experience in software development stands out as one of the main factors influencing resource decisions. Indeed, experienced developers  (those with at least 10 years of experience) utilise a more diverse set of resources to get information and stay up-to-date  about software development compared to developers that are just starting out and have less than 2 years of experience (utilising 3.5 resources on average vs 4.3 among experienced). However, it is not only the breadth of resources that varies with the level of experience, but also the channel preferences. For example, experienced developers lean heavily (52% vs 32%) towards vendor-driven resources  to stay up-to-date, whereas nearly half of developers with up to 2 years of experience rely on social media  for their information (vs 31% of more experienced developers).  Experienced developers prefer vendor-driven resources to stay up-to-date. The relatively high use of vendor-driven resources could reflect the fact that experienced developers have more responsibilities than their early-career peers. To explain, the pressure to ensure proper implementation and functionality can lead to a preference for official vendor materials - such as documentation, blogs, and newsletters - since these resources tend to be of higher quality and more reliable. Another reason that official resources are not so favoured among developers with limited experience could be that this kind of resources might demand better understanding of the subject matter and in some cases a deeper level of expertise, something that is also gained through experience. On the other hand, the prevalence of social media among early-career developers, in conjunction with their limited use of a number of fairly established information channels, could be due to a lack of awareness of those resources. For example, Q&A sites and conferences/events which are generally known among developers. Developers with little experience are also more likely to be utilising conversational AI services / chatbots than their more experienced peers (30% vs 22%). For many developers making use of conversational AI services, the combination of real-time interaction, breadth of knowledge and a “safe environment” (as you can ask basic, or even ignorant, questions without fear of judgement) are possibly compelling adoption points. These features, however, don’t seem to be particularly appealing to highly experienced developers. Amongst the rest of information resources, the use of open source communities and Q&A sites, as well as listening to distinguished peers, are top of mind among experienced developers. Information source preferences vary by region Another important separating factor is the region developers are based in. There are certain regions, where reliance on information resources is limited compared with others. For instance, countries in Asia (including China and Japan) exhibit a small degree of resource utilisations, compared with other areas (3.2 on average vs 4.2 excl. Asia). At the same time, developers within each region seem to have varying preferences in terms of which exact types of resources to use. For instance, Western European developers are significantly more likely to attend conferences or events than the rest of their peers (38% vs 25%) , whereas Latin American developers show a much stronger preference for social media and following respected peers than average (59% vs 40%). Similarly, CEMA-based developers are more likely to be using official vendor resources than developers based in other regions (47% vs 40%). In the US, official resources are used by 41% of developers, with community-driven resources (community websites, forums and groups) a close second. Importantly, maybe in light of the ongoing turbulence in the US labour market, a third of US developers prioritise education through attending seminars or pursuing training courses and workshops . Other characteristics affecting information resource selection for software developers   In addition to experience and location, the types of projects that developers work on is another factor affecting the preferences for information resources. More specifically, involvement in different project types might require developers to use different frameworks, technologies and/or programming languages. Thus, depending on the maturity, reliability and accessibility of each tool or service they use, developers may seek to retrieve information from different channels that best match each topic of interest, in order to optimise their level of understanding. For example, our data shows that web and backend developers, as well as those building apps/extensions for 3rd-party ecosystems, behave similarly  not only in terms of their information sources preferences but also towards the number of resources that they use (around 4.2 vs 3.5), when compared with developers in other sectors. Specifically, they stay up to date using a diversified portfolio of resources following both official/vendor-based (such as docs or forums) and non-official/community-based resources (such as Q&A sites or open source communities). So, any effective outreach strategy would likely need to extend beyond official documentation and require at least some level of presence on community-based channels  for these developers.  Another interesting finding is that more than one in three developers involved in ML/AI, embedded software development, or industrial IoT, are attempting to sharpen their skills through seminars, training courses or workshops , compared with just about 20% of AR/VR developers. AR/VR developers used to be more eager for training resources  (~33% of AR/VR developers in Q3 2023), broadly highlighting the current bifurcated state of the ML/AI and AR/VR sectors, as the former continues to see additional investments from companies because of the remarkable progress of generative AI models, and the latter being put somewhat on the backburner. For the vast majority of areas discussed earlier (excl. Latin America), results remain consistent across regions, meaning that these findings cannot be attributed to geographical location effects. More data, more insights! If you’d like to receive more data and insights about where developers go to find information, as well as what types of content they prefer, reach out to us  or explore all our research at the SlashData Research Space . About the author Lazaros Ioannidis Data Analytics Manager Lazaros has extensive experience in data analysis and research, with a background in financial markets. He holds a Master’s in Finance and is a CFA® charterholder. At SlashData he helps clients find data-driven insights to questions they must ask about their business.

Developer Marketing & Relations: The Essential Guide just published its 3rd edition Quick history: In 2018 SlashData decided to publish a book titled “Developer Marketing: The Essential Guide”, seeing the lack of education in developer marketing and relations roles and activities. In that book, industry leaders from the world’s largest companies shared their “things to do and things not to do” experiences. Each chapter had its own author, focusing on the topic they knew best. Fast-forward to today. Thousands of books have already been sold. The industry evolves fast. Not all ground has been covered. Therefore, an updated edition was much needed. This is why the “Developer Marketing & Relations: The Essential Guide – 3rd Edition” has been launched. The 3rd Edition features 9 new chapters and 1 revised chapter since the first 2018 edition. It is a much more complete read and covers most of the topics that dev marketing and DevRel professionals will come across in their professional life. The book can be read cover to cover or readers can pick the topics they are interested in. Each chapter addresses a specific topic written by an author from a major company. Some of the topics are community (+ how to make it inclusive), building personas, building developer programs, developer events, connecting with developers and many more from 24 authors and 17 Industry-Leading companies. The book’s aim is to educate and help professionals push their careers forward. All profits from book sales are donated to worthy organisations: Code.org, Girls Who Code, Black Girls Code and CoderDojo. So far we have donated more than £7,000. To support the dev marketing and DevRel community at challenging times, the book price is reduced by 50% to make it accessible to everyone: $9.99 for the paperback and $4.99 for the digital edition. The book is available through Amazon in Paperback and Kindle  and through the book website in ePub . For more details, see the book website. If you are a journalist and want to spread the word and/or write a review of the book, you can claim a free copy . Companies the book authors work in: Amazon Web Services, apidays, ARM, Atlassian, Facebook, Google, Microsoft, Nutanix, Oracle, Qualcomm, Salesforce, Samsung, SAP, TomTom, Unity, VISA, VMWare #book #developermarketingresources #devrel #developermarketing #resources #devrelresources

The Developer Nation survey If this is the first time you heard about SlashData, I’m happy to share a few quick words. SlashData is a developer research company. Every quarter, SlashData runs a survey on the globe developer audience, to measure the pulse of the developer ecosystem and how they feel about new technologies, tools, platforms, the support from developer programs and more. Following the closing of the survey, our expert analysts work on identifying key trends and translate raw data into actionable insights that professionals and companies addressing a developer audience can utilise to fine-tune their strategy and address developers’ needs and wants. The State of Developer Nation reports SlashData’s Developer Nation survey is the leading research programme on mobile, desktop, industrial IoT, consumer electronics, embedded, third-party app ecosystems, cloud, web, game, AR/VR and machine learning developers, as well as data scientists, tracking developers’ experiences across platforms, technologies, programming languages, app and API categories, revenue models, segments, and regions. The 26th edition of the Developer Nation survey reached more than 10,000 respondents from 135 countries around the world.  Now the results are starting to show. SlashData announces the first 2 of the 6-report series that are becoming publicly available to the world, showcasing and diving into key developer trends for Q1 2024 and beyond. Each report focuses on a specific topic. All reports published under the State of the Developer Nation will be accessible under the freshly launched SlashData Research Space , free to access, view, and download. Developer Research Report: How developers interact with AI technologies Has AI taken over the world? Not yet. However, it has achieved to both take over all our discussions about the future and have 59% of developers use AI tools in their development workflows.  This report investigates the current landscape of developers' work with artificial intelligence (AI) technologies and how this impacts their careers. We start by looking at the ways in which developers work with machine learning (ML)/AI models, tools, APIs, and services and highlight the key differences between professional and amateur developers.  Following this, we focus on professional developers and explore the correlation between working with AI and self-perceived promotion opportunities at their current jobs. Finally, we take a closer look at the developers who are the most likely to express intent of quitting or changing jobs in the next 12 months. “59% of developers use AI tools to help them with their work” To understand the current landscape, we asked developers about the ways in which they work with ML/AI models, tools, APIs, or services. We find that 71% of all developers are actively working with AI in one way or another. workflows, where using chatbots for answers to coding questions (42% of all developers) is the most popular direction.  You can access the full report for free in the SlashData Research Space. Developer Research Report: Sizing programming language communities  Which programming language has the biggest language community? It’s been a non-contest for a while for JavaScript, but it’s always fun to see how the community size has changed. The choice of programming language can greatly influence the roles, projects, and general opportunities that a developer has. Languages are a classic subject of debate and represent the foundation of some of the strongest developer communities. Tracking language use is not just for developers, however; languages and their communities' matter to tool makers too, as they want to ensure they provide the most useful SDKs. In this report, we provide estimates of the number of software developers using various important programming languages, across the globe and all kinds of programmers. We also explore the effect that coding experience has on the adoption of each language. “The JavaScript community grew by 4M users in the last 12 months” Here is a full breakdown of the size of programming languages communities: See how Rust is out to beat records and how the size of communities has changed over time in the full report . Developer Research coming soon As I mentioned before, we have a lot more coming. A combination of deep dives on key topics and free reports for everyone to access. Here are the reports that will be soon available and will complete the State of Developer Nation series:  How and why developers engage with emerging technologies How happy are developers with their jobs? Threats in software supply chain management Profiling of new ML/AI developers If you are looking to address a tailored question or want to take advantage of our expertise in surveying developers, let’s talk . Join our live webinar on June 25 to dive in together on how happy are developers with their jobs. Save your spot . About the author Stathis Georgakopoulos, Product Marketing Manager Always keen to see what’s next in the industry, Stathis is the Product Marketing Manager for SlashData, setting the table and running the marketing activities. He's our go-to guy for all things marketing and does not hide his love for content marketing and creating helpful content.

Games are one of the most popular forms of entertainment and gamers demand high-performance and cutting-edge designs. Performance is also key to developers who work on creating games. Considering the popularity of this entertainment niche, we take a look at how developers work on creating the games; more specifically: game engines. This article is based on “Game Engines and their use in Game Development” Developer Ecosystem Insights . In this report, we explore the state of game development and look at engines and the technologies developers use for creating video games. The embrace of game engines Around 42% of the developer population is involved in the games sector—either as a professional, student, or hobbyist. The developers have a wealth of technologies from which to choose, among which, game engines are the most prevalent. 47% of developers use 3D game engines; while 36% use 2D game engines. Some of these developers use both 3D and 2D, leading to a total usage of 60% of the game developer population. As the name suggests, the difference between 2D and 3D games lies in the number of axes of motion available to the players. In 2D games, there is no perspective, fewer possible movements, and therefore, fewer interactions with other characters or objects in the game—resulting in these games being typically less complex than 3D games. Do you need specific data on developers or the technology landscape? Contact us , and we will get these for you. 60% of game developers use game engines As recently as 2017, our data showed that developers used 2D and 3D game engines equally, with 44% and 45% usage respectively. In subsequent years, however, the chasm between the two has widened — by 11 percentage points. Overall, a similar percentage of developers are using game engines: 63% in Q2 2017, compared to 60% in Q1 2021. However, far fewer developers are now only developing games with 2D engines, which is down 7 percentage points from Q2 2017. On the other end of the scale, sole usage of 3D game engines is up 5 percentage points. The large rise in 3D usage is due, in part, to the impact of VR gaming; as well as the dominance of smartphone and native desktop games which, when coupled with modern powerful hardware and larger screen sizes, encourage increases in game complexity. The platforms targeted by developers who use game engines will be explored further in chapter three. Uneasy rests the head that wears the crown Unity has the largest share of the game engine market: 38% of game developers who use game engines use Unity as their primary engine. The next most popular game engine, Unreal Engine, has 15% usage as a primary engine—much lower than Unity. Unity’s dominance is clear, but the gap between Unity and its competitors is closing. Overall usage of Unreal Engine—both as a primary and an ‘also using’ game engine—is currently at 43%. In Q2 2017, it was at 20%. Unreal Engine’s focus on higher-end graphics and performance allows it to fill an important segment—their latest release of UE5 looks poised to continue this trend—but the engine is harder to use than Unity and is accessible on fewer platforms, somewhat restricting mass adoption. On the other hand, Unity remains king of the gaming market because it has succeeded in doing many things well: it is considered the best engine for mobile, excels in, and has a much larger and focussed tool-set for 2D games.49% of developers using Unity use Unreal Engine; while 76% of those using Unreal Engine find themselves using Unity. Traditionally, Unity’s versatility has not been easily replicated, but developers are currently finding success in combining game engines to access the unique advantages of each. Typically, developers use more than one game engine: 64% of developers using game engines are using two or more, and 38% use three or more . Developers using offerings from vendors with a smaller market share tend to use multiple game engines at the same time. The smaller engines often lack all the capabilities of Unity and Unreal Engine, leading to game developers mixing engines to find their optimal usage combinations. These engines’ market share comes predominantly from their role as additional game engines. For example, Godot has a 20% usage as a game engine which developers are also using, but only a 5% usage as a primary game engine. The reasons for the popularity of game engines are many, but one of them is the undeniable fact that game engines can shorten production time and costs. This makes this kind of technology more appealing than ever to a wide range of developers, ranging from amateurs to professionals, who are trying to gain a foothold in the industry. What are your thoughts? This data is just the tip of the iceberg or in gaming terms – a small tutorial or walkthrough. We have a lot more insights and data to share with you on games, including: where game developers work, how and where to reach them and even a forecast of their population for 2023. Access all data here We can go on this adventure together. Contact us

SlashData is a market research company. However, you do not need a market research company to tell you how much the technology space has changed in the past 5 years. Stories from post-pandemic times seem like centuries ago, yet they are not. It was just 4 years ago when the peak pandemic response was an influx of developers in the industry, creating products and services that could help transfer everyday life online. Then, Artificial Intelligence became an everyday topic. Every company is now becoming an AI-enabled company.  And these are just the last 4 years.  How do we respond to the changing technology industry? Being a market research company, we show what we see. Right now, what we see is that we can help technology leaders navigate through these times in new ways. With that in mind, we have taken significant steps to improve the value of our services to our customers.  “We are moving beyond developers, adding, decision-makers and users in the technology space, to the list of audiences we research.  The most important decision we announce today is that we are extending the audiences we research to beyond developers. Our research will also address decision-makers and users within the technology space and dive into understanding their behaviour and preferences.  Adding to what we are researching, not removing For almost 20 years, we have been known for our expertise in addressing software developer audiences and their needs. We will keep doing that. SlashData will always support software developer market research needs - our flagship. Our Developer Nation community will continue to be important to us and we continue our investments and relationships with developers globally. Decision-making has become more centralised, especially in the enterprise space. As a result, we have received increasing support requests to understand more about the people who identify as more than “coders.” This includes citizen developers, C-level, Senior, and Director-level decision-makers, and even retail users.  So, we are embracing the change. From now on, SlashData will be able to offer market insights on: CEOs, CTOs and C-level executives Citizen developers Senior and director-level decision-makers Retail users Broader technology audiences This way, we can share insights on the audiences beyond “software developers”. Audiences that interact and can bring change in the industry.   Dive into the full list of services we can offer. Get more from SlashData, your trusted market research experts Three years ago, we introduced custom research services: Custom Quantitative , Competitive Market Research , and Qualitative research . Since then, we’ve built a team of analysts, market research experts, and diligent project managers. Our workflow provides the infrastructure to run customised projects as smoothly as possible.  “Our in-house survey software and ML-powered methodology deliver cleaner than ever data” Going even further, our in-house survey software, together with our Machine Learning-powered best-in-class cleansing methodology, delivers data cleaner than ever and cleaner than any market research company out there can deliver.  We use it and can vouch for it.  The real question now is: what questions are you eager to answer? Let’s talk .  About the author Moschoula Kramvousanou is the CEO of SlashData. She leads the team and navigates the company through a rapidly changing space. She has been with SlashData for more than seven years, and took over as the new CEO in 2022.

Finding a balance between core business and serving your industry and the professionals through your expertise pro bono has been a challenge for many companies. Giving back to the community is hardwired into our DNA. The most obvious examples are the 27+ editions of our State of the Developer Nation reports, showcasing the key, emerging developer trends for over 15 years and a wide collection of free industry analysis reports, openly available on our Research Space. Then, of course, we also had DevRelX. How DevRelX started DevRelX did not start as a standalone effort. Around 2017, we had long worked with developer marketing and relations professionals, helping them understand developers through our research. At the time, DevRel was a very niche, emerging role, in need of a definition and a standardised set of responsibilities and requirements for the role. Naturally, this lack of given requirements created a lack of definition for the expertise required for the roles. Was it a marketing role? For some companies, yes, for others not at all. Was it a product role? For some companies, yes, for others not at all. You can see what I’m getting at. How do you know what you need to be proficient at in such a fluid role? It was our founder, Andreas Constantinou, along with the attendees of the Future Developer Summit and Nicolas Sauvage, who got together to gather the leading experts in the industry and create a book that would help newcomers in the field and seasoned veterans understand what is required from a developer marketing or DevRel pro. You can find more information on the book here . This book was the first resource offered. However, books are much slower to update with new information as it comes along. This is why we started a podcast series. Also, we ran webinars to present new data and trends as they came along. Now, all these resources were scattered around the web, but they were all addressed to the same professional struggling existentially. It was only natural that the handsome geniuses behind SlashData’s marketing team (myself included) decided to have all these resources in one place. And how about adding a few more stuff? Like job openings and an events calendar. Thus, DevRelX was born. The DevRelX Community DevRelX started as a hub. A one-stop shop selling nothing. Instead, sharing freely free resources. It was constantly updated with new content, resources, interviews and videos. Something was missing, especially since a pandemic had joined the equation. It was missing the human factor. People could visit the website to get answers, but could they learn from each other or find solutions to common problems? Not really. What we needed was…a community! A place for people to come together, learn from each other and connect. We provided the space and shared data and insights - what we know best. The community was growing as more people joined and shared resources. It became a place for learning and interaction. The DevRelX Summit How about we bring everyone together for an event, then? We had been hosting the Future Developer Summit as a private, in-person event for years. Now that the community was growing and events were going online, there was no sense in not opening it up for those hungry to learn and connect. Thus , the  DevRelX summit  was born, bringing together people who had knowledge to share, wanted to meet each other, chat, and have a fun, learning day. You can catch up on the Summit presentations on our YouTube channel: Full 2023 event "Driving impact at the Age of AI" Full 2022 event "Elevate the DevRel community together" The Closing of DevRelX “Wow, you make everything sound so nice and movie-like; why is the community closing?” Awww, I am much flattered, but if there’s one thing I have learned about community building, it is this: it needs to be a strategic priority, and it needs people to help it grow and evolve into what the community needs, and not what the company supporting it needs it to be. We are also evolving; we are growing to take on projects from “the road not taken”. This evolution forces us to take steps that bring us farther away from the core of the DevRelX community and its whole essence. SlashData will focus on what we know best: researching and understanding the world as it changes. Then, producing insights and transforming data in a way that helps everyone else understand it, too. Rest assured that we will continue to serve the industry through our data. We will continue to be a resource to help you and the leaders in the technology space get the data and insights they need for strategic decision-making. Come to us with your questions and challenges; we will always have an open door to explore how we can help.  We owe a massive “thank you” to everyone who took this journey with us. We are grateful for the lessons learned and the people we met.  See you all out there. PS. Not all is lost. We will keep sharing and updating the most important resources that our community loves: DevRelX resources that will still remain available Developer Marketing & Relations: The Essential Guide book The DevRelX podcast WeKnowDevelopers webinars The DevRelX newsletter will continue bringing joy to its subscribers until the end of the year (at the very least). Then, it will be moved to the SlashData newsletter . Data & Insights SlashData Free Reports Research Space Developer Marketing & Relations Communities DevMarketing Community DevRel Collective