Technographics, the next frontier for the ideal customer profile (ICP)
What are technographics and your ICP
If you're part of a mature go-to-market organization, you likely have a good handle on your ideal customer profile (ICP), as it's traditionally defined. You appreciate how much a well-defined ICP affects sales efficiency. However, there's a blind spot in the ICP development process that many orgs have yet to build out. Most go-to-market (GTM) teams have some intuition as to what technology stacks are predictive of successfully closed deals or leads that are unlikely to close, but they don't have data to support these intuitions and have no way of acquiring or analyzing this data at any real scale.
Credit: Gong
If a GTM organization knew exactly which technologies were in the "sweet spot" in terms of making a closed deal likely and which would make a deal impossible, would it improve their efficiency through better prioritization of leads? Would augmenting their ICP with this data improve the efficiency of marketing? We think so.
In order to close a greater number of deals more efficiently, sales and marketing teams ought to refine their ICP in this way. This is where Wappalyzer's technographics can help.
Refined ICP → more accurate lead scoring → more sales in less time
By integrating Wappalyzer with a CRM or marketing automation platform (MAP), teams will be able enrich all account data (customers, prospects, lost deals) with technographics. From there, teams can create reports directly in their CRMs or MAPs to identify patterns in the tech stacks of both their customers and their lost deals. They would also be able see how these answers might differ across other ICP variables like scale, industry, etc.
Almost every software company will find meaningful signal in these reports. What can be done with this information?
- Enhanced view of ICP will refine lead scoring algorithms.
- Salespeople will have leads that are easier to prioritize with a higher probability of success.
- Teams can avoid the dreaded time-wasting interactions that drag on for months only to end up with an implementation engineer saying "this is not going to work".
- Marketing content can be more targeted and relevant.
- Salespeople will have the ability to deliver personalized, differentiated messages, e.g. "We see that you're using technology ABC; we have a great integration with lots of customers that also use it and here are two relevant case studies".
Leveraging tech stack data to inform outreach will save time and money. For example, teams can use this information to tailor marketing campaigns specifically to the technology their prospects are using, improving interaction rates with outbound messages and ads.
Using this approach will allow teams to:
- Personalize their emails more effectively — send out emails that go beyond "hey, here's what we do" by referencing specific technologies used by their leads and customers.
- Save time on manual research — no need for tedious one-by-one research into prospect companies' systems or software platforms.
Tech stack data can help you build better prospecting lists
After establishing technographics as part of ICP development, and successfully using that data to improve the efficiency of an existing sales pipeline, technographics can also be used to improve lead generation and expand the top of the funnel.
For example, SDRs can create lists of companies that use the technologies of their company’s top integration partners. They can create lists of prospects that are already using a top competitor and avoid reaching out to them (if they are in a low-churn, high-switching-cost market). Account executives at Mixpanel, for example, may choose to avoid reaching out to companies that they already know are using Amplitude, and vice versa.
Conclusion
If you're reading this, chances are that you already know how important tech stack data can be for your GTM organization. However, the fact remains that most businesses have not yet found a way to generate these insights at scale. We hope we've given you a better understanding of why tech stack data is so valuable and how it can help improve your GTM organization's velocity and efficiency. If nothing else, we hope this post has given some food for thought! Please feel free to reach out with any questions.
