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5 Actionable Tips for Weaving Your First- and Third-Party Intent Data into Killer Campaigns

Aug 20, 2019 | Author Yvonne Haendel

TL;DR - Many companies have invested heavily in the martech stack and content to harvest and act on extensive first-party data. Some companies invest in third-party intent data for various use cases including demand generation. Great companies combine the two data sources to unlock really powerful playbooks and tactics. Here’s how.

Data Pangea

A quick trip back to middle school science: Remember Pangea? Pangea was the “super continent” that existed before tectonic plates began shifting and the continents as we know them spread around the globe.

That’s our vision for fully integrated intent data. We believe that optimal results will be achieved from integrating first-party and third-party intent data. In some cases, it may even make sense to interpolate multiple sources of third-party data.

That’s aspirational for most intent data prospects and customers.

What’s fully within reach, however, is an active integration of first- and third-party data.

First-, Second- & Third-Party Intent Data

Let’s quickly level set.

First-party intent data is the information you already collect about behaviors across your digital footprint. This includes details of website visits and interactions, engagement on your various social channels, and email opens and clicks. You might also use call tracking and other tools which contribute additional first-party data signals.

This is the “digital body language” that your marketing and sales teams rely on for segmentation and pre-call preparation and opportunity/sales intelligence.

Second-party intent data is like first-party data but owned by someone else. A common example is lead generation programs offered by industry publishers. They have opted-in subscribers and sell programs and/or individual leads based on interactions with their subscribers and specific content. It’s limited to their own publishing platform and audience.

Third-party data covers all sorts of actions elsewhere on the web. The objective is to identify accounts where there’s a surge in activity and specific details on individual actions. It’s important for demand generation efforts that face challenges including small percentages of potential buyers actually in market (3% is a common estimate), low conversion rates on inbound marketing leads, and lots of competition for attention in crowded ad spaces.

Third-party data often has inherent limitations. Normally it’s anonymous, account-level signals only. That helps for ABM prioritization, but not for targeted, personalized marketing and sales approaches. It’s also often missing specific context. (Topic-level data built on opaque taxonomies limits important insights.) Further its often collected from a limited range of sites — often a publishing coop — and misses vast volumes of important signal from elsewhere on the web. Some data may also conflict with various terms of service.

IntentData.io addresses all four of these with GDPR-compliant data harvested from structured and unstructured publicly available information across the entire web. Our Contact-Level™ Intent Data includes specific detail regarding the type of action a lead has taken with regard to your products and services.

This contact-level insight creates special opportunities for marketing and sales when it’s combined with the first-party data you already collect.

The Intersection of First-party Intent Data with Third-party

Common digital marketing playbooks call for tactics like lead-scoring, progressive profiling, persona-based segmentation, nurturing workflows based on form submissions, and matching contact and interactions to inferred stages in the customer buying journey.

Those tactics generally help marketing teams move IQLs (information qualified leads) to MQLs (marketing qualified leads), eventually nurturing them into SQLs (sales qualified leads) and handing them off to sales to begin a sales process. Now we can add a new category - intent data qualified leads. Let’s call those IDQLs.

Best practices involve weaving together a number of signals, drawing inferences from them, and reacting — often with personalized automation and sometimes with specific sales responses.

For instance if you observe a prospect repeatedly visit a page that lists features and pricing for an enterprise version of a product, but then request a demo/quote for the SMB version, it’s likely that your AE’s will be prompted by that information to explore the larger goals to sell what’s probably the better solution for the buyer: the enterprise product.

Similarly, when a prospect says they’re ready to buy, but only spends seconds on each page of a proposal, spends the most time on the price page, and then ghosts you, you’ll likely review the qualification process to understand what you missed.

This is approach is powerful. But it has a huge limitation. It only observes the engagements within your digital footprint. You don’t have insight into other members of the buying team that haven’t hit your site, nor interactions with competitors and independent research with related content elsewhere on the web.

Our first-party data can be rich, informative and exciting.

It’s only a fraction of the data that our marketing and sales really need to complete the picture and nurture and sell with maximum effectiveness.

And that’s the opportunity of overlaying third-party intent data on top of your own first-party data.

5 Tips to Make the Combination Payoff

As soon as companies shift their thinking from seeing third-party data as just a demand gen tool and look at the opportunity to combine it with first-party data, a huge number of tactical plays open up. The options are really only limited by your creativity, sales and marketing collaboration, and perhaps the sophistication of your marketing automation.

Here are five simple ways to use third-party signals to supplement your own first-party data.

  1. Identify other buying team members and influencers - By observing signals and associating them with pending deals/opportunities, marketing can score big points with workflows that notify AEs. Important information includes not only the names and contact details but also the titles and nature of the action. Sales, in turn, can use this info to coach their deal champion on other perspectives within the company and provide appropriate enablement content.
  2. Observe competitive interactions - Competitors’ digital marketing will attract and engage some of the same prospects as ours, but also different subsets. Whether those are known to us (in which case this is an important signal) or unknown (a new set of prospects active in the market that we didn’t know about) it creates various opportunities for segmentation and messaging focused on frequent competitor claims and our USPs.
  3. Personalized experiences - You may already use first-party data to personalize customer experiences with dynamically generated content and tailored playbooks for chatbots and conversational marketing. Now imagine being able to refine those further with information which you’ve observed but contacts haven’t shared. If you know the competitors they’re engaged with, the other topics they’re researching and other roles in their company that is participating, you can deliver far more effective personalization.
  4. Very early-stage engagement - By identifying early-stage research actions, marketing can help BDRs target possible prospects. Email and paid social ads can be used to create/observe engagement and in this case, the first-party data, which follows the initial third- party signal, can be used to segment likely prospects.
  5. Churn reduction - You’ve certainly got lots of first-party data about existing customer contacts, but do you know who else in the company might be itching to find a different solution? Are your main contacts sharing everything they’re thinking? Are contacts from your customers attending competitors’ events? What about utilization factors: are there any warning signs? Third-party data can help to identify both accounts at risk and the contacts in play, but also up- and cross-sell opportunities

Bonus tip: Retargeting - Why do we limit retargeting to those that have triggered our own pixels? With third- party data on key areas of interest, event attendance, and competitor interactions, you have the ability to retarget based on external factors. By incorporating first-party data insights such as topics that they’ve engaged with on your site, you’re able to build custom audience segments to deliver perfectly tuned paid social messaging.

An Orchestrated and Activated Approach

Too often we see companies buy intent data as a demand gen tool only. It’s powerful for that, and when properly activated, it’s incredibly effective. We’ve seen results as dramatic as an 82% reduction in sell cycle and 50% close rates.

Really effective companies, though, go beyond that. They use data for a variety of use cases across the customer lifecycle, and they combine the wide-ranging third-party data signals with their own carefully harvested first-party data.

The result is a much richer understanding of individual contacts and account-level initiatives — and when that understanding is translated into specific marketing and sales activity, the outcomes are powerful and exciting.

 

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