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 intent data 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 or Two Use Cases
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 or two use cases that will drive quick results.
Most teams first focus on account prioritization. This allows your sales team and business-development reps (BDRs) to allocate their time and efforts — e.g., calls, emails, event invites, etc. — to the accounts currently researching your products and services, and thus most likely to buy. In turn, these teams benefit from a reduction in both wasted time and the length of sales cycles, ensuring greater revenue contribution from current resources.
When your initial pilot use case succeeds, move on to the next, following the same guidelines outlined below.
Related Article: 5 Lesser-Known Ways to Use Intent Data for ABM
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.
As Jeff Marcoux, VP of marketing at TTEC, stated in a recent presentation on how to successfully expand the use of intent data throughout the marketing and sales funnel, “Intent data is not just a technology, it’s also a culture shift. Training is critical — train early and train often.”
Be sure to develop the steps needed to educate anyone who will be using the data. Any good intent vendor will facilitate this process via tutorials, knowledge base 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 topic clusters 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. Moreover, you should ask any intent data providers you’re considering what kind of functionality they may have regarding a historical buyer journey analysis.
Related Article: Help! I Don't Have the Data I Need
Understand the Topics Most Important to Monitor
Intent data usually works by monitoring specific topics or clusters of topics to determine whether an account is “in-market” (i.e., looking to buy a product or service). So, selecting the right topics 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 (i.e., fewer topics per cluster). 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 sophisticated with your clusters.
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 create a cluster of 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 (SLAs) 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, comprising a mix of topic 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 the 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.’
Related Article: Account Based Marketing: Digging Into Facts, Uprooting Myths
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. As mentioned before, Fortinet ran its pilot program manually and had great results. 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.
Another great tip from Jeff Marcoux’s recent presentation: “Don’t boil the ocean to start.” 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.