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A version of this article was originally published on CMSWire.As with any new technology investment, marketing and sales teams need to show wins, quickly. Deploying third-party intent data can seem particularly challenging, because it has such a wide range of use cases that can affect numerous systems and workflows.
This can leave some teams feeling overwhelmed or unsure as to how best to get started. But don’t let this deter you. Having a sound strategy in place before deploying intent data can ensure a quick, smooth path to success.
These guidelines will help you develop a successful and scalable intent strategy.
Start With One Use Case
It's easy to want to go big and fast with intent data. Its numerous use cases support the entire customer lifecycle—from top-funnel advertising to mid-funnel account prioritization to post-sale customer expansion. The possibilities are enticing, but it’s a good idea, initially at least, to focus on one use case (maybe two) that will drive quick results.
Most marketing and sales teams first focus on account prioritization. This allows your business-development reps (BDRs) to allocate their time and efforts to the accounts currently researching your products and services, and thus most likely to buy.
Another great use case for B2B marketers to start with is intent-activated lead generation. This lets you acquire intent-qualified leads from target-account decision-makers who have requested to download your branded content.
Both of these use cases are easy to get up and running quickly without the need to integrate numerous systems or revise any existing processes. When your initial pilot use case succeeds, move on to the next, following the same guidelines outlined below.
Ensure All Involved Teams Are ‘Bought-in’ and Understand Goals, Strategies, and Tactics
Marketing commonly invests in intent data for the initial use case of account prioritization—only to discover later that sales isn’t using it effectively. This comes down to communication. Not only must department leaders be convinced of intent data’s value, each user of the data must fully understand how to leverage it in their daily activities—as well as how it will benefit them.
Be sure to develop the steps needed to educate anyone who will be using the data. Any good intent data provider should be able to facilitate this process via content and/or direct guidance.
Gather Baseline Performance Metrics and Buyer’s Journey Intelligence
Baseline Performance Metrics
This seems obvious. But in my experience, organizations that document this are in the minority. This is understandable, however. We use so many technologies today that identifying a baseline metric against which we can measure the impact of every deployment can be overwhelming.
Yet, identifying even just one performance metric per use case can tell a lot. For example, Alan Tarkowski, senior director of Global Sales Development at Fortinet, recently discussed his first foray into using intent data. Before fully deploying intent data and automating workflows via integrations, Tarkowski and his team wanted to first test the data manually. His team documented various pre-intent performance metrics—including account-list conversion rate and BDR sequence replies—in advance of the pilot program. This enabled Tarkowski and team to quantify the program’s results and make informed decisions regarding whether and how to scale the program. As he put it,
“Knowing our baseline performance allowed us to quantify the value of the intent data. We found that BDR email open rates jumped 122% and BDR sequence replies multiplied by 7 times. More importantly, our conversion rate for targeted accounts to booked meetings increased 33%. Seeing these results enabled us to pull in more resources to further automate the program through integrations and scale results.”
Buyer’s Journey Intelligence
This one is a bit more difficult, but powerful if you can accomplish it. Identifying a common research path among your target audience—i.e., trends and correlations that exist among specific search terms, content subjects, asset types, product/feature interests, etc.—can help you select the right topics and customer keywords for specific use cases throughout the funnel.
There are various ways to accomplish this. Gathering first-party data from your CRM, marketing automation, and customer-data platforms is a good first step. (Intent data should always be used in tandem with your first-party data anyway.) Customer interviews can further provide useful context regarding the typical buyer’s journey.
Understand the Topics Most Important to Monitor
Intent data usually works by monitoring specific topics and/or keywords to determine whether an account is “in-market” (i.e., looking to buy a product or service). So, selecting the right topics and keywords to monitor is critical for success.
A good rule of thumb: the higher the use case is in the funnel, the broader and fewer the number of topics you should monitor. This will ensure you’re casting a wide enough net for the purposes of, say, advertising. Inversely, as your use cases move down the funnel, you’ll want to be more specific with your topics and keywords.
For example, say you’re first using intent data to support your programmatic advertising campaigns to promote a document-management product. You’ll want to monitor two to three topics that may be shared by a broad product category. Such topics may include “document sharing,” “content/document management” and “document security.”
But for your second use case, such as prioritizing sales-accepted leads (SALs) by account, you’ll want to be far more specific with your topics. Otherwise, you won’t achieve enough granularity to properly rank accounts. In this case, you’ll want to select seven or more topics and customer keywords, comprising a mix of topic/keyword types: product names, competitors, benefits, use cases, etc.
Align Your Intent Strategy With Related Initiatives
Developing your intent data strategy in a silo will only hamstring your results. Even if you’re deploying a limited pilot program, think about how the specific use case can be used in the context of other tools, data, and strategies.
Let’s take predictive modeling and account-based marketing (ABM) for example. You can use intent data for ABM in numerous ways. But here are two specific ways it can support account prioritization alone.
- First, you can attach intent data to accounts with ‘fit’ to further prioritize accounts; this ensures greater efficiency while also providing sales reps or BDRs with more info, enabling more relevant and meaningful conversations with target accounts.
- Second, you can run a separate campaign to identify net-new accounts that may currently fall outside your ‘fit’ parameters due to lack of enough first-party data. This is particularly useful for organizations with a limited total available market (TAM). Not only will this increase sales pipeline (because you’ll convert previously unknown accounts), it will also provide further information with which to continually refine your predictive models and hone ‘fit.’
Identify Any Potential Integrations or Opportunities for Scale
It’s not imperative to integrate intent data with any systems or tools relative to your initial use case. However, the right integrations will amplify intent data’s benefits (such as efficiency) and impact (such as revenue contribution).
It’s a good idea to think continually about how to better leverage the data—whether through an integration with your CRM to improve ease of use and analysis, or by expanding to additional use cases, such as identifying opportunities to expand current customer accounts.
Intent data has the ability to support the entire customer lifecycle, while also increasing the value of your other martech and sales-tech investments. This makes a focused intent data strategy even more important.
Taking an incremental, thoughtful approach to your intent data strategy is well worth the effort. Used wisely, intent data can benefit numerous teams and departments, increase customer satisfaction, and help your business scale quicker than you thought possible.
