There’s one best practice for marketing to software developers. It’s to not market to software developers. There’s no other way to put it, and I can’t make it more clear.
If you’ve worked in B2B or tech, you’ll understand precisely what I mean. Most engineers and developers hate “branded messages” and corporate marketing jargon. They aren’t afraid to publicly call companies out for their interruptions. And if they don’t call you out, they don’t notice you.
The other best practice for marketing to developers and engineers is to start with data. The more you can think like an engineer and understand what motivates them, the better you will be to create a relatable story. The truth is that data-driven content marketing and social media storytelling are the only full-proof way to precisely reach this highly technical audience.
Below is an example of an analysis done about two years ago. These insights are applicable today and could inform programs, content, and marketing to software developers, engineers, programmers, etc.
An Analysis of Engineers & Software Developers
Our analysis uncovered nine distinct and unique software developer audience segments. This audience was created using bio search with unique self-identifiable key phrases like software developer, software engineer, and programmer coupled with programming languages like Python, C++, C Sharp, Java, Front-end, and Back-end.
Understanding different audiences’ behavior is essential to predicting future content marketing opportunities. For example, software engineers do not like being marketed to, so B2B companies must provide content that adds value to the conversation. Social media analytics platforms can dissect audiences and understand the software developer audience’s keywords and phrases, topics they talk about, and the media publications they read.
Not All Software Developers Are Created Equal
The software developer audience is unique. They are not fans of marketing and will call you out publicly if you aren’t providing value and justice spamming on social media. Below is a quick snapshot of the unique interests and characteristics of this specific software developer audience.
The below audience segmentation is just a subset of the nine audiences from the initial analysis. They are segmented on how they describe themselves in their bio, their conversations on social media, and which technology and software applications they follow on social media. You’ll notice that each segment’s top influencers and media preferences are different. This is why it is critical to segment audiences in this fashion.
Language Analysis of Developers Can Uncover Hidden Narratives
Below is a topical conversation analysis of the audience. We took one of the software engineer audience segments and clustered all their conversations over 12 months. We analyzed 12.5 million social media conversations and clustered them based on volume. So, when researching this particular developer audience, they talk about five core topics: data science, machine learning, cloud, Azure, and big data.
Each of the subtopics is color-coded and has three layers. The layers represent a drill-down of each of the subtopics. So, when looking at data science, the context of the conversation revolves around AI, research, and machine learning. When looking just at AI, you’ll notice full stack and Python. Clustering data helps contextualize what is essential to the software developer audience and what they care about.
What Media Outlets do Software Developers Read?
The below data represents what media publications this segment of software developers read and share online. There are three data points plotted below.
The X-axis represents the mention volume. In other words, it shows how often software developers share articles from these media publications. The Y-axis represents the total number of engagements from those specific media mentions. The size of each bubble means total impressions. Total impressions in this context are the aggregate sum of all the followers from every person engaged.
Here are a few examples that might help illustrate why this is important.
When software developers read an article from Enterprisers Project, which isn’t often, it generates very little engagement from the developer’s audience. Also, the aggregate volume of followers from those individuals is small for those who did engage with the article.
Another example is when software developers read and share articles from DZone. While the volume is much higher than some other publications, engagement is still minimal even though the reach of that content is larger.
And lastly, when software developers read and share articles from MIT Technology Review, it generates excellent engagement and reaches a larger audience.
This type of analysis can inform a lot of different marketing and public relations tactics and programs. For example, this type of data can inform a PR strategy and prioritize which traditional media outlets to go after based on the audience you are trying to reach.
More Analysis of the Software Engineer Audience
A few years ago, I analyzed software engineers. Instead of starting with a Boolean search to find/export conversations and then try and isolate the audience, I reversed it. I built an audience first, added them to the audience panel in Brandwatch, and then analyzed their conversations.
The audience database consisted of about ~6K self-identified developers, programmers, and engineers. This was done mainly by combining bio and shared content data. For example, I used “developer OR engineer OR programmer” as bio terms and cross-referenced those accounts with shared topical data like Hadoop, data science, and python. This method ensured I found software developers instead of commercial real-estate developers and chemical or civil engineers.
I ran the list through Audiense and further segmented the developers to understand what I was working with. I discovered the following sub-segments within the audience panel–IOS Developers, Microsoft MVPs that are using Azure, VMware vExperts, PHP Developers, Game Developers, Data Scientists, and Security/Hackers.
This content analytics approach is meant to isolate the conversational data and drill down on the topic areas that were top of mind for each sub-segment. The data showed that the top trending topics among this developer audience revolved around nine core areas–artificial intelligence (AI), big data, security, IoT, machine learning, blockchain, data science, DevOps, and deep learning. I used these insights to create filters within Crimson Hexagon and isolated the data further within a historical context. I pulled data from 1/1/17 to 6/1/18–roughly 18 months, resulting in 16.5 million posts (or conversations) among the 6K software developers.
Here’s what I found:
Developers are all over artificial intelligence. AI leads the way in terms of total volume, followed by Big Data, Security, and IoT. You’ll notice that Machine Learning and Deep Learning have separate data points. They were purposely excluded from the AI analysis to get the most accurate view. Similarly, both AI and Deep Learning were excluded when analyzing Machine Learning.
Conversational Topic Analysis
The real value comes when analyzing topical data within the audience panel. For this post, I only extracted the top media publishers developers are reading and sharing based on five of the nine topics listed above–artificial intelligence, big data, security, blockchain, and data science. The publishers are sorted based on total interactions from the developer panel. Higher interactions typically mean that the content resonated with those reading it.
The following data represents the top five media publishers that developers read and share when talking about and sharing news related to artificial intelligence.
The following data represents the top five media publishers that developers read/share when talking about and sharing news related to big data.
The following data represents the top five media publishers that developers read/share when discussing and sharing security news.
The following data represents the top five media publishers that developers read/share when discussing and sharing blockchain news.
The following data represents the top five media publishers that developers read/share when discussing and sharing data science news.
Oh, and a few bonus audience insights here. Developers prefer Spotify as a music service. They often share playlists of melodic heavy metal and EDM (I had no idea there was such a thing) with their friends and colleagues, so they can also concentrate when coding. They also share a lot of long-form content from LinkedIn blogs and Medium; much of it is content they wrote themselves.
How is This Data Actionable?
Well, it depends on who you are and what you do. If you work in public relations and you want to reach software developers, you can start to dissect the above media publications, build a media list and prioritize your media outreach. You can also begin aligning your messaging and narrative to one or more of the above topics, assuming they are related. You may also consider submitting an executive byline to one of the publishers. Or, you can pay $1,200 to Forbes, join their technology council, and post content that way.
If you work in digital marketing, you may consider a media buy or sponsorship on a few of these sites since you know the developer audience is spending time there.
For those who work in social media or content marketing, you can build a custom audience and target content to this group with minimal paid investment.
The Real Value in This Data
The social data above accounts for 18 months of conversations, sharing, and engagement. It’s great for historical context and understanding the trending conversations that are peaking and the ones that are declining. To make this data more useful, I would consider listening to what the audience is saying and responding in real-time. This will help brands be more relevant among the people that matter. This approach is a strategic replacement for what many brands still do today–creating content calendars for weeks in advance, going through days of approval processes, and scheduling posts using automated technology. There is little to no value in doing it this way, especially when all the social content links purely to owned media (blogs, white papers, etc.) offer very little value to the developer community.
The Best Practices for Marketing to Software Developers
Marketing to software developers presents some unique challenges. First, developers are often skeptical of advertising and marketing claims. They are used to seeing hyperbolic language and exaggerated features in product marketing, and as a result, they can be challenging to reach with traditional marketing techniques. Second, developers are usually very busy, and it can be challenging to engage with long-form content.
Instead, it is often more effective to focus on creating helpful content relevant to their work. Developers are highly knowledgeable about the products they use and often have strong opinions about what features are important to them. As a result, it is essential to ensure that your marketing messages are clear and accurate. By following these best practices, you can create more effective marketing campaigns that reach and engage with software developers.
1. Be concise and speak their language. When marketing to software developers, it is essential to use language they will understand. This means using industry jargon and technical terms in your marketing materials. It also means avoiding overly sales-y language or exaggerated claims. Developers are used to seeing marketing materials full of hype, and they will quickly tune out messages that sound like they are trying to sell them something.
2. Be accurate. Don’t try and BS the developer community. They will see right through it and call you out if you try too hard.
3. Build trust. Be real. It’s helpful to have a developer consult with your marketing team so they can help you craft messages that will add value and not appear to be marketing messages.
4. Use data. When marketing to software developers and engineers, it is essential to use data to back up your claims. This data can come in customer testimonials, case studies, or third-party research. Using data in your marketing materials can show potential customers that you have a well-rounded understanding of your product and that facts back up your claims.
As you can see from this analysis, several insights and actions can be taken that can inform a B2B marketing strategy when marketing to software developers or any technical audience.
It’s important to note that software developers are very technical individuals and have conversations on social media. They don’t like when brands interrupt the conversation with marketing material. Therefore, you must create content that delivers value if you are a brand and marketing content for software developers. This means utility or technical documentation that helps this audience solve a particular problem.
In many cases, it’s good practice to have internal executives and subject matter experts be the ones to engage with software developers. When the conversation is authentic, software developers are more likely to open up and have an open dialogue. Activating executives and subject matter experts would be a part of an employee advocacy program. There are several influential developers online who are very active on social media. As part of your influencer engagement strategy, one thing to consider is to build contact based on what is top of mind for them through real-time influencer listening and engagement.
Influencer marketing and employee advocacy are just two best practices to market to software developers. However, considering several other things as part of a B2B social media marketing strategy could be practical.
Several platforms provide this level of detail when analyzing audiences. You should consider making similar investments into technology if you are marketing software development.
It would help if you were innovative and strategic when marketing to software developers. It requires strategy alignment, stellar execution, and a solid measurement approach. I hope you enjoyed this content. I do my best to create actionable content and provide value to your work.
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