Relying on Intent Data Alone: More Harm than Good?

leadspace b2b customer data platform

Three out of four B2B sales and marketing teams rely on intent data to prioritize ABM outreach. Intent data is incredibly important as it provides insight into which companies are searching for you – i.e. which companies are demonstrating some level of intent to use your type of product (or specific product). While that’s useful information to have when trying to put the right type of content in front of the right companies, it simply doesn’t paint the full picture necessary to target deals in the B2B world. In fact, intent data can even point us in the wrong direction and inspire our sales people to confidently follow a rabbit hole that goes nowhere fast. Let’s explore how to use intent data effectively and avoid diving head-first into a pit of bad leads.

What is intent data?

Intent data tells you when companies are actively researching online for a solution, and which products and services they are interested in, based on the web content those companies consume. Marketing and sales leaders that use Intent data have an advantage by understanding which companies are ready to buy – and avoid wasting time and money on those that are not.

There are 2 major types of intent – first-party intent and third-party intent.

First-party Intent data is information collected about your audience or customers from your internal programs and digital properties:

  • Behavioral data, actions, and interests shared across digital environments such as your business’ website or app 
  • Data collected in your CRM 
  • Data from subscription campaigns 
  • Information collected from social media efforts
  • Offline surveys, forms, and questionnaires

Third-party Intent data is information collected from outside sources that provides an external view of that company’s intent. There are several ways to source third-party intent data, and it’s important to use a trustworthy source that’s transparent about the methods of collection:

  • Behavioral data, actions, and interests shared across digital environments from a cooperative of publishers, websites and apps
  • Bidstream data that originates from a publisher’s website or app that passes some site visitor and page-level data  during the real-time bidding process for programmatic advertising
  • Behavioral data collected by a publisher’s owned and operated network of websites and apps

Why is using intent data by itself not effective?

Regular intent data tells you which companies are searching globally for the intent topic(s) (keywords or phrases) that you’ve selected within the confines of your intent provider. For example, your intent data might indicate that people from IBM are searching for a specific topic that you’ve ranked as a high priority, which is great to know – but it doesn’t tell you who, or even what region, those searches originated from. On the other hand, there is metro-level intent data which provides further insight into the specific metro area that those searches are coming from. 

While metro-level intent data provides a deeper layer of accuracy, it still doesn’t paint the picture you need to effectively target the right people within the right companies with the right content at the right time. A company might be searching for your product, but that doesn’t mean they’re even likely (from your perspective) to buy your product. Are they a big enough company? Are they in the right industry? Are they B2B? Do they look anything like the companies you’ve closed business with in the past? Essentially, do their demographic, firmographic, and technographic makeup indicate a company who is likely to buy your product? Searching for your product doesn’t indicate ability to buy. With intent alone, you’ll know people at a company have searched for your product, but you don’t know if that company “fits” your product. Do you even want IBM? It’s great to know who is interested in your product, but that doesn’t tell you who to actually focus your time, money and effort on. To effectively target closeable business, we need visibility into all of those qualifiers, and filter them in the correct order. Before we dive deeper into the problems with using intent data by itself, let’s explore the correct steps towards identifying closeable business.

What’s the best way to identify closeable business?

There are 4 steps to successful B2B targeting – applying four AI-models across your Total Addressable Market (TAM) to effectively score, filter and prioritize closeable business:

  1. Propensity = the right companies
  2. Intent = the ready companies
  3. Persona = the right people
  4. Engagement = the ready people

It starts with discovering your TAM and generating your Ideal Customer Profiles. The next step is determining which companies to go after. This involves using your historical first-party data to develop an Ideal Customer Profile (ICP), then comparing it throughout your TAM with an AI-based propensity model. By determining how closely each target company matches, or ”fits” your product, a propensity scoring model predicts the increase or decrease in the odds of a successful conversion. This is the first stage of honing-in on the best companies to target.

The second step is determining which of the companies are actually ready to buy. This is where an intent scoring model is used to determine intent at the product level – ensuring it’s the right time for the right company. We determine intent by a company’s search activities. Many of you may be buying weekly intent feeds delivering the names of companies who are searching for the terms that you prioritized. Knowing that a company’s employees have been actively searching in your field of expertise with either new high intent or sustained intent enables you to focus your efforts on the best companies that are truly ready to buy.

The third step is figuring out who are the right people to pursue within those companies by scoring their personas. Does their role at the company line up with the personas of your historical successes? Is their persona typically responsible for making decisions to buy your type of product or service? Who makes purchasing decisions at the company? Or who might see the value in your product and bring it up the chain of command quickly and effectively? With a persona scoring model, you can narrow in on the department, level, right job title, role or expertise to go after by identifying the right person in that company who is most likely the right contact for your type of product.

The final step in prioritizing closeable business is applying an engagement scoring model to those personas, or specific people at the company (or buying center), to identify which of them are actually ready to buy. This means scoring their engagement at the person-level, using your marketing automation platform – Marketo, Eloqua or Pardot, for example. Has that individual been on your website? Who specifically has been searching for your type of content, or has engaged with your previous marketing efforts? With this final piece of information, you can focus on the right people from the right companies who are ready, able, and eager to buy your type of product or service – ensuring you don’t waste time, money and effort chasing down leads that aren’t likely to close.

What are the risks (costs) associated with using intent data alone?

The main issue with relying on intent data alone is that it doesn’t indicate a company’s likelihood of buying your product.  Usually, companies will give intent to their sales people, who just open up their sales list vendors and search around through the companies that showed intent and guess at who would be good to reach out to – confidently spending their valuable time and resources chasing down leads without even knowing whether that company is actually a good fit for their product. Additionally, with intent data alone, sales people typically won’t have any visibility into the specific people who searched for their product within those high intent companies.

Essentially, using intent by itself encourages your salespeople to kick off a semi-random search for companies to reach out to, spending money buying contacts then eyeballing job titles (which isn’t the best way to pick the best buyers to begin with) not even knowing if the title’s are correct and up to date. They don’t even know which ones have already been lit up by their sales/marketing teams. They’ll likely do all of this in ZoomInfo without even looking at their own database or leveraging their historical first-party data and ICP as most companies don’t connect their Marketing Automation Platforms (Marketo, Eloqua, Dynamics) to their Salesforce instance – missing out on important historical context to the leads they’re pursuing.

The opportunity cost of aiming at the wrong company and person when time is of the essence is significant. Start with sales teams spending hours a week searching around.  Add to it the hard cost of money spent on license costs from popular sales list vendors (such as, LinkedIn Navigator), etc. It all adds up.  Investing those resources would be worth it if the business was closeable, but with intent alone, salespeople don’t even know if it’s closeable! Sales people getting it wrong means zero return on their effort, and not meeting their quotas. We want to ensure our salespeople get it right – that means giving them more than just intent data. With intent alone, we risk the likelihood of not closing, wasting time and effort pursuing bad leads, passing on bad information for ABM targeting to our marketing team, and wasting money on data licensing. How much time do sales people spend searching for contacts based on incomplete signals? Intent is critical to driving closeable business, but it’s incomplete/insufficient.

How to use intent data effectively? By using it in combination with other models!

In short, intent alone is not really closeable intent if the company doesn’t match your ICP. Intent data is incredibly valuable, but only if you’re applying it to companies that already fit your ICP, which most of us fail to do. Additionally, intent doesn’t take you all the way to the exact persona and specific person or buyer to pursue within a company. To effectively use intent data, we need to first identify accounts with high propensity, then apply our intent model, then apply persona and engagement scoring models to truly hone in on the right person within the right company at the right time to best improve our odds of closeable business and minimize the waste spent on pursuing leads that aren’t likely to pan out.
Intent is a lot like using a flathead screwdriver on a Phillips screw. It’s better than nothing and can work in a pinch, but it takes a lot more effort to make it work and it can ultimately damage the screw. For more information on successfully applying propensity, intent, persona, and engagement models in combination to identify the companies and the people within them who are ready, willing, able, and eager to buy your product, check out the Leadspace Revenue Radar Guide and hop on the fastest road to revenue today.

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