The Market Research and Product Management functions at many of today’s technology companies are spending hundreds of thousands, even millions, of dollars on big data and analytics to better understand customers and prospects. Yet, much of the data and answers they seek are already collected and synthesized by their own marketing program teams as they perform lead generation campaigns – they just don’t know it.

By feeding lead generation campaign results into Market Research and Product Management, technology companies can develop offers and products that far more effectively attract new customers and grow revenue from their existing customer base.

Let’s take a look at the makeup of your lead gen results and how they can easily inform Market Research and Product Management, without changing the way you currently run lead gen campaigns.

Lead Gen Results are Great Market Data

When we perform lead generation campaigns on behalf of our marketing clients, we query customers, prospects, and partners around a large number of product and service criteria. Not only do we find out which products and services they want, we also find out such information as why they like them, which products/services they dislike, why they dislike them, and how they view competing vendors. Their responses are a treasure trove of data.

What Typically Happens to Lead Gen Data

Let’s face it – when a customer or prospect indicates that they have little interest in your product or service during a lead gen campaign, their contact information gets relegated to the junk heaps of ‘Not Interested’ or ‘Dead Target’. That fact should horrify market researchers and product managers.

Why don’t these customers or prospects have interest in your product/service? What makes them feel that way? What attracts them to other products/services? In most cases, these people have provided direct answers to those very questions in a survey-driven lead gen campaign. But since marketing program managers have no incentive to share that data – instead being evaluated solely on the volume of marketing qualified leads (MQLs) they produce for Sales – they simply do not share that information with anyone beyond the marketing programs team.

How to Ensure Meaningful Campaign Results

Before launching a lead gen campaign, inform the market researchers and product managers of your campaign goals, target audience, and topics. If the campaign is to include a survey, obtain input from Market Research/PM regarding the specific information they would like to know, tweaking your questions in order to glean ideal responses from your targets.

Of course, not all lead gen campaigns use a survey. Many campaigns are minimal and involve little more than an email of a new offer or invitation to learn about a product/service. Nevertheless, the results from these types of campaigns are also valuable to market researchers and PMs. For example, let’s say your company developed a new product and is offering it via a campaign to your existing customer base. Market Research and Product Management would love to know about specific customers and where they fall on the spectrum between showing great interest and showing no interest at all. By merging these lead gen results with already-known customer profiles, researchers and PMs can quickly identify ways to improve the product, its attributes, and even the way in which it is offered or packaged with other products and services.

Regardless of the type of lead gen campaigns you execute, your marketing program manager for each campaign should align with Market Research and Product Management before campaign design. Having input from those teams will allow marketing programs to make slight modifications to the campaign design, and those could greatly improve the value of the data collected.

You Don’t Know What You Don’t Know

Now that you have a high-level understanding of the value of lead generation results, you will want to become adept at collecting and sharing the most valuable data and findings with Market Research and Product Management. For that, I will dedicate an entire blog post and delve into the details of how to serve up the ideal data sets, synthesized findings, and target account specifics. So, stay tuned and check back soon for that post. When it is completed, I will also add a link to it here.