Buyer Intent Data for Industrial Sales - Warnings and Tips

Ed Marsh | Nov 1, 2023

Understand What Buyer Intent Data Is, Then Whether / How to Use it

Introduction to SignalsFromTheOP

Guide to Episode

  1. Intent data is an interesting tool for sales and marketing that helps you observe actions around the web which may indicate that someone is in market to buy your products
  2. There are different models of intent data - you have to understand the details
  3. Buyer intent data is not a silver bullet - you need to understand what's required to operationalize it
  4. There are several use cases that will work for industrial sales - particularly around a list of targeted or focused accounts

Transcript follows:

Hello. I’m Ed Marsh. This is SignalsFromTheOP, my biweekly video series that provides early warning of important industrial sales and manufacturing marketing topics for owners and leaders in industrial manufacturing firms. Please check out the full playlist and share this with others who you think might find value.

Let’s talk about whether buyer intent data fits into industrial sales, and if so, how to implement it and what to expect.

In order to tackle that, let’s first level set.

What is buyer intent data? Buyer intent data is a category of information that is intended to help you understand who might be in market for what you sell. In contemporary usage, it’s mostly digital.

That being said, you’ve used intent data for years. For instance, if someone visits your trade show booth and then returns later with some colleagues, that’s important intent data. Obviously that’s a set of signals that is meaningful and which you add to your qualification analysis in addition to the details of your conversation.

First Party Buyer Intent Data

Since that engagement happened with you, we call it 1st party intent data.

You have lots of other 1st party data.

  • What people visit your website
  • How often they come back
  • What pages they visit, even what pages in what order
  • How many people from the same company visit your site in any rolling period of time
  • What job titles those people have
  • Who engages with your social media
  • Who opens and/or clicks marketing emails, or sales emails
  • Who spends what time on what pages of your proposals

All those are examples of 1st party intent data that can be meaningful to your sales team in terms of prospecting, managing open opportunities, etc.

It’s collected by your your sales tech stack and marketing automation systems, and salespeople must be coached on how to interpret and use the data.

2nd Party Buyer Intent Data

You probably have some 2nd party intent data too. If you do any trade journal advertising, and get leads sent to you with info on what actions the journals registered users have taken, that’s second part data. Like your first, but on someone else’s digital property.

3rd Party Intent Data

3rd party intent is what most people actually mean when they say buyer intent data. This is what’s happening everywhere else on the web. For instance, with competitors, thought leaders and influencers in your space, etc.

There are various models for collecting and reporting 3rd party intent data.

While there’s some tech detail and inside baseball, it’s important to understand the differences.

One model is a publishing coop. This is a group of online publishers who get together and agree to share information on what their registered users and visitors are doing and reading on their sites. This means that data from this model is limited to those sites. It’s at the account level only (since it’s anonymous) and it often relies on IP address resolution, which is imprecise. Typically, the data is categorized, and one limitation is that there’s normally no insight into what details they’ve jammed into the taxonomy for a category. You might think it’s relevant or irrelevant, but there’s no way for you to gauge.

Another model is bidstream data. This is a by-product of engagements that people have with online ads. Essentially, it’s a series of guesses that if someone from a company is shown an ad, and we think we can guess the type of content that was next to that ad, then we can assume that they’re interested in the topic of that content.

There are some problems here. First, the cascading assumptions. It’s an absurd extrapolation. You probably aren’t even aware of most of the ads you see, and they’re probably not relevant to what you’re reading. Also, the data is very high volume and low accuracy, and there are real issues with privacy since data that you never agreed to have sold, is now being sold. The WSJ recently had an article on bidstream data and government surveillance, and the Senate Committee on finance had targeted bidstream data before COVID disrupted their oversight.

Our model crawls the entire public web, including all structured and unstructured data, and identifies content that matches your specific criteria by competitor, key term, etc. Then, when we see people engage with that content publicly, we capture those signals. We resolve who the person is from their public profile, and report on their activity and the details.

This is unique. It’s contact level intent data, and it is accompanied by enough detail to interpret what it means – for instance, the stage in the buying journey and the problem someone’s trying to solve.

Using Intent Data for Industrial Sales

Intent data is not a silver bullet. There’s a lot of inaccurate and misleading data sold and outrageous claims made by vendors. For instance, intent data can’t tell who’s searching for something online. And even when data is accurate, it’s easily misinterpreted. I may be reading about something or sharing something that I have no intent of purchasing.

Nevertheless, it’s valuable info – for the right companies with the right marketing and sales infrastructure. What does that mean? These are my insights after five years of intensive work with intent data.

It’s not a sales lead list.

If you use buyer intent data as a list to call, you’ll waste money, creep out prospects, and sour your sales team on the leads marketing sends them. That’s true regardless of whose data you use.

So if you’re a typical industrial manufacturer – let’s say a $200MM in revenue with a one person marketing team and 15 sales reps – there’s only one reasonable way to use it. That’s to watch for activity in target accounts, customer accounts, and accounts where you have pending deals. You need to set a high threshold for what constitutes activity – remembering that many providers send anonymous and inaccurate signals, and even accurate signals aren’t necessarily indicative of readiness to purchase.

And then, you need to understand your third-party intent data as an additional source of info. It augments your first-party data and other information, and it’s a signal that your sales team should consider in their analysis of the account and what’s happening. That’s going to take sales enablement and sales management effort. It’s going to take the required sales and marketing data stack. And it’s going to take a sophistication among the sales team.

So don’t get oversold on buyer intent data. It’s not a simple lead list. And beware of long contracts that lock you in, and some of the bazaar pricing that seems to exist in the market. If you’re trying to decide, I’d suggest skipping it. If you think you have an organization that could benefit, I’m happy to share my insights into data, models, and industrial sales to provide some helpful perspective.

I’m Ed Marsh. If you found value in this episode of Signals from the OP check out the full playlist and maybe even like it, share it and subscribe – either to my YouTube channel EdMarshSpeaks.TV or at the related blog