Intent data is a complex product. It’s also a relatively new product category. Further, it’s one of the “hottest” products in B2B marketing, supporting numerous use cases throughout the buyer’s journey.
Understandably, marketers have a lot of questions. Below are my thoughts on the most important intent data questions I hear on a regular basis.
Is All Intent Data Pretty Much the Same?
There are numerous types of intent data. Even if we take a narrower definition of intent data — for example, excluding first-party data such activity on your owned web properties or email engagement — there is still a sizable range of sources, tracking methods, and scoring models.
Regarding third-party intent sources, the most common include data originating from:
- Ad exchanges (or the bidstream).
- Individual online media companies (or publishers).
- Co-operatives of web properties.
- Social media platforms and public data.
- Peer-review websites.
Personally, I think companies’ engagement with your owned web properties, social profiles, and email should also fall under the definition of intent. And even if not labeled as intent, such engagement should most certainly be leveraged alongside third-party sources of intent.
Regarding tracking methods, intent data vendors usually have customers select among specific topics and/or keywords. (See Question 2 for more on the differences between the two.)
Scoring models also vary. Some simply provide the number of “events” associated with particular keywords or topics. For example, they may show that a targeted company consumed 43 pieces of content in the past week that include a specific keyword. Others provide an algorithm-based score that compares recent content-consumption events against a historical baseline of research activities.
The important thing to note is that no one intent source type, tracking method, or scoring model is necessarily better or worse than the others. They’re mostly all complementary to one another. With each variation, you get a different piece of a giant jigsaw puzzle, uncovering your target market’s needs and buying intentions. The more types of intent data you use, the greater your intent signal coverage, because you’re casting a wider net across online web properties, and signal accuracy, because you can verify intent signals against multiple sources.
Related Article: What Separates Intent Data Success From Underwhelming Results? Actionability
Are Intent Topics and Intent Keywords Just Synonyms?
It’s important that anyone using intent data understand the differences between monitoring intent keywords and intent topics. When you track keywords, you're looking for the use of exact words or phrases within a piece of content and/or its URL. If, for example, a blog post includes the keywords a marketer is tracking, and a business user reads the article, that activity then registers as an event that will help inform whether that business is showing intent.
Tracking topics, on the other hand, looks at the entire piece of content to assess its relevance to one or more pre-defined subjects (i.e., topics). Such relevance is typically identified using natural language processing (NLP), a subfield of machine learning that focuses on the interactions between computing and human language.
There are pros and cons to both keywords and topics.
- Pro: Allows for more customizable intent targeting, which is especially helpful when trying to identify intent around niche products and services.
- Con: Doesn’t account for the contextual relevance of the entire piece of content being consumed, which may lead to a false-positive intent signal.
- Pro: Accounts for contextual relevance of content consumed, mitigating the likelihood of false-positive intent signals.
- Con: Must be selected among an existing topic taxonomy, which may not include the topics you wish to track.
For these reasons, it makes sense to leverage intent solutions that monitor both topics and customized-keyword activity.
Related Article: 3 Ways to Improve B2B User Experience With Intent Data
What Are the Biggest Ways People Incorrectly Use Intent Data?
Generally, the biggest issue I see is teams investing in intent data but then failing to implement processes to act fully on the data insights.
More specifically, I see teams use intent simply to prioritize target accounts for a specific engagement channel or tactic — and that’s it. For example, a marketing team may use intent data to prioritize which accounts sales-development reps (SDRs) should focus on, but not provide information relevant to which messaging is most likely to resonate with contacts from those accounts. This is an enormous waste. Analyzing intent signals to understand which messages, content, talk tracks, etc. will appeal most to prospects is one of the key benefits of intent data.
This problem is often — but not always — a consequence of functional silos in organizations. For example, a demand generation team will adopt an intent data solution for a single use case, such as identifying businesses to target for a content syndication initiative. They may even use the intent insights to inform their follow-up tactics for leads generated via that effort (a second use case). But then they’ll neglect to share that data with other teams that would find value in the data. Digital marketing teams could use the intent insights to improve ad targeting or messaging on social channels. The revenue operations team could use intent signals to improve account-scoring models.
Don’t get me wrong — immediately implementing intent data across every possible use case will usually end in disaster. It’s much better to take an incremental approach to scale its use.
However, the gradual expansion into various use cases throughout the buyer’s journey should be part of your intent data strategy. In other words, intent data can drive better results throughout the entire buy cycle, so why limit its value to one or two use cases?
Related Article: How to Use Intent Data for Content Marketing
How Do You Connect Company-Level Intent Data With Decision Makers?
Third-party intent data solutions mostly — though not always — provide insights at the company level, rather than the contact level. This is due to various factors, ranging from intent-derivation techniques to sensitivity regarding data-privacy regulations.
Obviously, marketers and sellers need more than company-level information. That’s why using intent to improve targeting for lead generation initiatives (such as content syndication) is so valuable — you get content-level data from intent-identified accounts without running afoul of data-privacy regulations.
Once you have contacts in your database, leveraging data integrations (e.g., with CRMs like Salesforce) enables you to append intent scores to individual decision-makers at your target accounts. Though these intent scores are based on the target account’s aggregate content-consumption activity, analyzing such company intelligence alongside the contact’s individual engagement activities provides very useful information.
Where in the Buyer’s Journey Is Intent Data Used, and How?
The short answer: almost everywhere.
Intent data can support use cases from the very beginning of the buy-cycle (e.g., branding via programmatic advertising) all the way down to post-sale account expansion efforts (e.g., identifying when customers are ready for to cross-sell). Pretty much any marketing, sales, or customer success effort that relies on knowing when a company is “in market” to buy and what they’re interested in will benefit from intent data. (Here’s an overview of the lesser-known intent data use cases.)
Moreover, intent data can help you identify where your target accounts are in their buyer’s journey. Analyzing the research activities of your target accounts against specific types of topics or keywords can indicate their funnel position.
For example, when a company is spiking on topics or keywords related to challenges, problems, or pain points, that usually indicates the account is early in their journey and simply trying to better understand their challenge. However, when a company is showing interest in topics or keywords related to specific brand names or product names, it indicates the company is further along their buyer journey, and considering specific solution providers.
These are just a handful of important questions that frequently come up during my conversations with B2B marketing and sales teams. If you have any questions about intent data, reach out to me and I’ll be more than happy to try to answer them.
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