In my previous article, I discussed the first of three important questions to consider if you’re unsure of whether it’s the right time for your organization to invest in intent data. As a refresh, these questions include:
Now I’ll address the second piece: having a sound strategy in place. Building an intent strategy before deploying your solution(s) will help ensure you’re getting the most value from your investment.
Unfortunately, many marketers are struggling with forming data strategies in general, as an Ascend2 research report found that over half of respondents (55%) said they don’t currently have a strategy in place for unifying their data. And it can be especially challenging to confidently make marketing decisions when working with a new tool—another report found that the greatest challenge intent data users are currently facing when using the tool is “creating a strategy for its use” (43%).
So, here are eight key elements of a successful and scalable intent data strategy.
After you’ve defined your organization’s needs and the initiatives you want intent data to support (see Part 1), start with one or two quick-win use cases to focus on. You’ll typically want these to be marketing-driven use cases, since marketing often owns the intent data investment and implementation.
Many teams start with account prioritization for paid media campaigns (e.g., content syndication, digital advertising, etc.) as it allows you to strategically allocate time, effort, and budget to accounts that are currently researching your products/solutions—resulting in better engagement outcomes and increased return on ad spend.
Once you have these initial marketing use cases dialed in, you can then expand to additional ones. For example, you can layer intent data as a criterion for your account- and lead -scoring models or optimize sales outreach by using the intent signals to dictate which messaging or business development reps (BDRs) should use to engage prioritized accounts.
During the pilot run with each use case, be sure to measure results, so you can analyze what’s working and identify where any roadblocks may exist. Take these learnings and then optimize your efforts. Of course, this depends on having pre-existing benchmarks set.
It’s important you set baseline performance metrics prior to implementing your intent data to understand what’s working and what needs attention.
To measure the efficacy of your intent-driven initiatives, analyze and document your pre-intent performance for any use case for which you plan to leverage intent data. For example, if you’re planning to use intent data to support third-party demand gen campaigns, such as content syndication, you’ll likely want to track some or all of the following:
Once you’ve gathered enough data on the performance of both your pre-intent and intent-driven programs, compare the results. You can then quantify the value of your intent data investments—helping you make more informed and thoughtful decisions regarding when and how to scale your programs.
This is true of B2B marketing efforts in general, but it is even more important when using intent data solutions. Effectively engaging prospects in a longer sales cycle means being thoughtful and strategic about the information you’re serving them. Understanding where they are in their buyer’s journey will help you select the right tactics, content, and messaging to use for each target account—creating better prospect experiences, increased conversion rates, and consistent pipeline growth.
Having a solid understanding of the buyer’s journey is particularly important for intent data success because the signals can tell you where prospects are in their journey. And you can then use these insights to better provide targeted accounts with the information they need, when they need it.
For example, accounts that are actively researching topics and keywords that generally relate to challenges (rather than products, solutions, or brands) are usually much earlier in their buyer’s journey. With these accounts, you would typically want to focus on top-funnel engagement tactics (e.g., programmatic advertising, content syndication, etc.) with messaging related to the challenges they’re researching—rather than brand or product specific messaging.
Of course, to do this you must have assigned your content and messages to relevant buyer journey stages. (Read here for how to use intent data to accurately align content to target accounts’ interests.)
Keep in mind that experiences shape the way prospects (and all of us) absorb ideas. Try to put yourself in your prospects’ shoes to understand what they’re experiencing as you create content for them. Finally, don’t forget to avoid common content marketing traps that can undermine your efforts.
As I mentioned in the last paragraph, intent signals can help you identify where prospective customers are I their journey. But that benefit requires you to track that right intent topics and keywords. For this reason and others, it’s vital to be strategic when selecting intent topics and keywords.
Far too often, however, marketing and sales teams simply prioritize any account that spikes on a few terms related to their brand and product offering. While this may help you identify some in-market accounts, you’ll end up wasting a lot of intent data’s value, such as:
A good rule of thumb is to monitor both topics and keywords, as this is the best way to ensure contextual relevance of the content being consumed (topic tracking) and targeting precision (keyword tracking).
It’s vital marketing and sales teams are aligned before you implement intent data, as they are typically the main users of the tool (customer success teams are arguably just as important). But research shows there’s still work to be done—the previously mentioned Ascend2 report found the top three complaints from BDRs/sellers regarding intent data’s use are all consequences of poor sales-marketing alignment—with “lack of message alignment with marketing” (42%) being the second contender.
If you’re using intent data for sales-related use cases (e.g., engaging prioritized accounts with customized messages) in addition to those owned by marketing, both teams must be on the same page and know what intent data is, its core values and various use cases, and how to optimize processes to get the most benefits. Because it’s a domino effect, if teams aren’t aligned and inefficiencies are undermining marketing’s efforts to drive sales pipeline (whether in quality or quantity), then sales has a much more difficult time closing new deals and acquiring new customers.
Ensuring there’s an established hand-off process that equips sales with appropriate intent-identified messaging to use on prioritized accounts is critical. Persistent communication, education, and training are also key. Finally, don’t forget to include all stakeholders and other relevant departments in these discussions such as customer success and media agencies.
Again, it’s all about the strategy. A good demand gen plan leverages a variety of different channels and tactics to help your target audiences understand their challenges, become aware of how your products/solutions can solve them, and ultimately, purchase from your organization. And intent data solutions can help with all of these.
It’s important to understand, document, and communicate to all relevant teams and individuals how you plan to use intent data—on an incrementally scaling basis—to improve your demand gen efforts. This can include, but certainly isn’t limited to:
Even while deploying a limited pilot program for one use case, you should think about how you can take your learnings and apply them to other use cases. Further be sure to think about how intent may support other tools, data, and tactics you leverage for those use cases.
For example, if you’re currently using intent data for sales efforts (e.g., identifying which accounts to focus on and which messages to use with each), think about how you can so the same with customer success efforts—such as identifying which accounts are a churn risk (based on their research of competitor solutions) and what you need to focus on to prevent losing a customer (e.g., which products/features are they researching?).
Though this isn’t imperative, it’s always a good idea to think about how you can better utilize intent data—whether it’s through an integration with your marketing automation platform (MAP) or CRM to improve ease of implementation, or by introducing intent to adjacent teams who would gain value from it.
In Part 3 of this series, I’ll discuss the most common resources required to support intent-driven efforts, specifically focusing on employee time and skill, and core technologies.