Content + Intent Data: Informing Content Based on Interest

Jon Russo intent data
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We recently gathered 10 intent data experts and power users and collected their tips and insights in The Content + Data Connection: 10 Top Marketing Executives Explore the Rewards of Integrating Intent Data into Content Strategies.

To keep that conversation going, we’re posting a series of Q&As with those experts to share their perspectives on how content marketers can make the connection between data and content.

Informing Content Based on Interest

Jon Russo, Founder and CMO of B2B Fusion Group, also joined us for a recent panel discussion, sharing even more of his perspective. As a former CMO for several high-tech brands, Jon knows firsthand how crucial content is to successful ABM programs. B2B Fusion has developed industry award-wining ABM experiences for its clients.

Here are his predictions and words of wisdom about the integration of content and intent data.

Do you see opportunities for more B2B brands to use intent data intelligence at the foundational stage to formulate their content strategies?

There are multiple types of intent, but for purposes of this conversation I’ll describe account-level intent and person-level intent and provide the use cases for account-based intent.

A buyer “interest” set can be developed, similar to a persona, where intent data can inform what content to target based on the interests of the buyer at that time or, in some cases, based on actual articles consumed (and when exact article consumption is known to the seller).

Intent can be used as an ingredient in the determination of a Marketing-Qualified Account (MQA). If an account is showing high interest based on topics, it could qualify or score high enough to become an MQA for sales to further qualify.

Intent also can help sales significantly—for example, if the sales team has a large number of accounts in their territory, intent can help prioritize those accounts for them. Intent can also help identify accounts in a buying process that are not in a defined Ideal Customer Profile. So it can expand the target market.

How should the different data types be applied to content strategy?

First-party intent data is known intent data—data such as de-anonymized web traffic, cookies, web visitors, content that is gated or other form-fill activities. App usage and product usage data could also be considered first-party data. Gated content may be research reports from analysts like the Gartner Group, so may be better suited for top-of-the-funnel content strategies.

Second-party data is someone else’s first-party data. Publishers who have content they own (G2, TechTarget) would be examples of opted-in of use of content. An example of a content strategy would be targeting bottom-of-the-funnel activities for those using G2 Crowd to make comparisons of vendors. This would also be a situation where you know which data is being consumed by the buyer.

Third-party intent data is everything else that happens on the internet—for example, web search terms, syndicated content. Keyword searches and topics expressing high interest could be gathered at the account level and then retargeted based on interests of that end user. Targeted content syndication is typically found at the top of the funnel (Pre-MQAs or leads).

How are B2B companies using intent data to inform the content they’re creating in terms of topics and formats?

In theory, a progressive company could use intent data to facilitate personalization at scale.  Although there are few B2B statistics published in this area, B2C companies have a similar struggle with personalization.

Forrester conducted personalization research that found that even companies whose personalization processes and approach are immature still see benefits. More specifically, companies that personalize, according to Forrester, can see a 6% increase in revenue, a 33% increase in customer loyalty and an 11% marketing cost savings. So intent-data information could be used to help with personalization.

Our clients use intent data as an ingredient in the “cake” of an MQA. So if a certain account score is achieved via intent or engagement, the account becomes Marketing Qualified. After Sales takes this MQA, the sales team may discover that the budget or timing is not right for the client. At that point, they are disqualified as an MQA and are returned for a top-of-the-funnel content nurture or targeted web ads that are intent driven. Conversely, if they are further qualified beyond an MQA, we can then channel content that is more relevant mid and bottom of the funnel.

How do you recommend B2B revenue teams ensure their sales teams are getting the right content in front of the right buyers?

For contact-level intent data, the ability to understand how different titles of people engage at different stages in the buying journey or what job level is likely to appear first, indicating intent can also be helpful around targeting content at the buyer. This requires quite a bit of manual intervention in its current form, or some analysis, but would be valuable for product marketers.

You can also use either contact or account intent data to broadly monitor trends in the industry to create content around that aspect. You could use this information to pitch PR topics to key influencers or reporters, which helps position your company as a thought leader in the space.

What advice do you have for brands that are just starting to apply intent data to content strategy?

The first challenge is making sure the keywords you’ve selected are the most relevant. Some of this work should already be done with your SEM search. The second is the integration to the CRM system, or in some cases marketing automation (though most integrate to CRM systems) to make the information or data collected usable by both Sales and Marketing.

If the keywords are on the accounts, some marketing automation systems may or may not be able to read those fields and target the contacts within those accounts—which may be another challenge. Lastly, someone has to map the keywords, topics and high-interest areas to the buyer’s journey, then create the content to be served at those points.

Are there any use cases that demonstrate how intent data has been effectively integrated into a content strategy?

We treat intent very differently in our clients beyond content use cases. We treat it as powering the MQA. This gives us more clarity around intent ROI, as its impact is very measurable. It will be more “squishy” to measure the content ROI with intent data based on how systems are used.

How do you see intent data helping B2B marketers develop content that’s customized for unique accounts and target buyers?

I could see a model where intent data really helps a firm that has a channel marketing strategy where they may not control the end customer, but they can target the end customer with relevant content based on their intent. By doing this, they’d not upset their channel partner yet still create their own demand for their product.

There is a more powerful model that some of the providers are at early stages in testing. Almost an “easy” button that leverages intent data for BDRs/SDRs. For example, if a buyer is exhibiting a certain behavior and the intent platform deems them as qualified, BDRs are instructed what plays or steps should be taken in terms of content presentation.

Right now, this requires some level of manual intervention to program the platforms for this, but this takes all the guesswork out of BDRs having to figure out what content to serve. With BDRs, given how junior they are, this approach really empowers them more cost effectively.

In our recent panel, Why Intent Signals May Be the Missing Ingredient in Your Content Strategy, we discussed the intersection of intent data and content with Latané Conant, VP of Marketing at 6sense, Nirosha Methananda, VP of Marketing at Influ2, and Jon Russo, CMO and Founder of B2B Fusion Group.

For additional perspectives, read our interactive E-book, The Content + Data Connection: 10 Top Marketing Executives Explore the Rewards of Integrating Intent Data into Content Strategies and our previous Q&As with Jon Miller, John Steinert, Latané Conant and Justin Keller.

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