Intent data shows which leads or accounts are actively conducting research online. As they search, they’re scored on thousands of topics. This data is used to alert sales and marketing teams when their high-fit accounts are in buying mode for their particular solution. When used correctly, intent data dramatically boosts conversions and sales.
Why do marketing and sales teams love intent data?
Intent data is a powerful predictor of which accounts are ready to buy. To use a sports analogy, if firmographic data shows where all the players are on the field, intent data shows what they’re each about to do next.
Intent data is rarely used alone. Knowing that a lead is interested in a particular topic isn’t very useful unless that lead is also qualified to buy. That’s why intent data is often paired with firmographic, technographic, and other data which narrow the list of accounts to just those that are high-fit.
When research on a particular topic spikes in activity (is significantly higher than usual), the account is shown to ‘surge’ on those topics. Sales and marketing teams should prioritize accounts that are surging on relevant topics over equally qualified accounts that don’t show intent.
What are the different types of intent data?
There are two types of intent data, both of which use a combination of IP addresses and browser cookies to track visitors online.
1. First-party intent data
First-party intent data isn’t anything new: It comes from tracking your website and is often called engagement data. Many marketing automation platforms have produced first-party intent data for more than a decade now and most marketers have access to it. First-party intent data can be anonymous, meaning there’s no name associated with the record, or it can be known, meaning the individual has filled out a form and has provided their name and contact information.
2. Third-party intent data
Third-party intent data is a much newer category. While marketing automation tracks your own web properties, third-party intent data providers can track everyone else’s. Bombora, for example, operates a data co-op which collects data from thousands of high-value analyst sites like Gartner, review sites like G2Crowd, and publications like Forbes. When your prospects research on those sites, Bombora indicates that they are ‘surging’ on particular topics.
With a combination of first and third party intent data, marketing and sales teams can improve the success of their outreach. If a sales team knows the topics a particular account is researching, they can send more relevant messages. And if a marketing team knows the context behind that research, they can personalize their website and nurture content.
Here are common uses for intent data:
- Build targeted account lists – Sales and marketing teams can dynamically filter outreach lists for accounts that show active interest.
- Account-based marketing (ABM) – Sales and marketing teams can select ABM accounts based on their level of research and account-wide intent.
- Personalization – Marketing and sales teams can better personalize initial outreach with resources that match whatever accounts are already looking for.
- Targeted advertising – Intent data can be used to deliver more targeted ads to both known and anonymous prospects.
Where does intent data fit into my scoring model?
Intent data is best combined with other forms of data. Companies can use an all-in-one data provider like EverString to bring many data sources together and build an account scoring model.
EverString provides the data to determine account fit plus intent through an integration with Bombora. Through another integration to marketing automation providers like Marketo and Eloqua, EverString can access engagement data to profile companies in this workflow:
- Fit – Which accounts fit our ideal buyer persona?
- Intent – Which accounts are researching valuable topics?
- Engagement – Which accounts have engaged with us?
ABM software company Terminus has pioneered the use of this scoring model for ABM:
“To succeed with ABM, get data-driven with Fit + Intent + Engagement to select accounts, prioritize what needs to be worked on now, and promote effectively and intelligently.”
— Peter Herbert, VP of Marketing at Terminus
Where can I buy intent data?
First-party intent data comes from marketing automation providers such as Marketo, Eloqua, and others. Each of these platforms use similar methods for collecting data, but give you varying degrees of access to it. For example, Marketo’s scoring feature allows teams to grade contacts and accounts on very granular behaviors, and can penalize them based on negative factors such as irrelevant job titles. Others do not.
When choosing a marketing automation provider, include “flexible scoring model” and “intent data integrations” among your criteria.
Third-party intent data comes from vendors such as Bombora and TechTarget. When evaluating data providers, here are a few crucial questions to ask:
- Does the data map to leads, accounts, or both?
- How is the data collected?
- How broad is the coverage and how granular is the detail?
- Can the provider deliver context? That is, do they provide a breakdown for how the scores are calculated?
- Does this data integrate into your existing marketing system, CRM, and scoring model?
Intent data works best when blended with other sources
Intent data, like any data, is not infallible. If you use intent data to focus only on buyers who show intent, you’ll invariably exclude some buyers who are interested but who are not captured by the intent data provider’s model. For example, some high-value prospects may conduct research on out-of-network sites or might be registered under the wrong IP address.
Too much focus on intent data can also lead marketers to prioritize quick wins at the expense of building a sustainable pipeline. Intent data works best when paired with other data to create a holistic scoring model that also reflects fit and engagement.
If used in the right balance, intent can be a powerful predictor of which accounts are likely to buy.
Originally published at everstring.com
— Published in INTENT DATA on January 10, 2019