Winning a battle for sales productivity – Improving quality of your data

In this blog post you will learn how an established data quality process can boost sales productivity, what to expect from data enrichment and data validation vendors and practical advice on data quality models. Please note that If your sales team currently consists of just a couple of people and your marketing engine’s generating just a handful of leads per day, you may want to bookmark this article and get back to it in a couple of months or years depending on how fast your company’s growing.


Over the last 10 years of managing digital marketing and sales operations teams at B2B software companies I’ve been in many battles. Off the top of my head, I would call out a battle for visibility (improving the attribution of bookings and pipeline to leads from paid marketing channels), and a battle GDPR for compliance – when GDPR came into fruition in 2018 and forever changed the culture and rules of communication between vendors and their customers and prospects.

But by far the biggest battle I’ve been challenged to win pretty much every business I’ve been part of, has been the battle for the sales productivity. In my experience though, for a B2B software or SAAS business this battle doesn’t start until a company reaches a certain size or a certain level of maturity of their sales and marketing engine.

The battle for sales productivity indicates maturity of sales and marketing

In particular, until the sales team starts aligning their account executives or business development representatives with certain territories or until the lead generation engine produces more leads than what the sales team can handle.

Picture I - An example of distribution of sales territories (geographical areas of focus) - United States of America


When I mention sales productivity for B2B software and SAAS companies, what I really mean is the sales team’s ability to qualify the leads generated by the marketing team in a way that provides lead-to-opportunity and opportunity-to-won conversion rates necessary for a company to hit its top line number.

I think my sales operations colleagues would agree that the biggest impact on sales productivity in every mature B2B software or SAAS business lies in the accuracy of lead routing (or lead distribution) and effectiveness of the lead scoring.

Sales productivity = 50% lead routing + 50% lead scoring

From there we’ll focus our attention on the lead routing and how marketing and sales operations leaders could improve its accuracy and speed to ultimately improve sales productivity. But before, let’s make sure we’re talking about the same things.  Lead routing implies a process of delivering an inbound lead to a sales person through CRM for further qualification based on so called lead routing (distribution) rules. An example of a very basic lead routing rule for B2B companies could be one that sets up distribution of leads among the sales team based on “HQ Location” or  “Number of Employees” or “Vertical (Industry)”.


There are two crucial parameters indicating the quality of your lead routing – precision and speed. While all of this sounds simple and easy, I think this time again my colleagues from sales ops would agree that precise and fast lead routing is a non-trivial task. It’s been half a century since we sent astronauts to the moon and yet delivering a lead to an appropriate sales person in a short period of time remains a challenge.

Key indicators of the quality of your lead routing – precision and speed

The reason why accurate and fast lead routing is such a challenge lies in the foundation of modern B2B lead generation. Marketers would collect information provided manually by leads on lead registration forms and then sales ops would trigger lead routing based on that data. Fields such as Full name, Business email address, Phone number, Company size and Vertical (industry) information would be typically required before leads could proceed to downloading content, products, etc. On top of that they would also collect HQ location by either scraping it from the GEO IP or adding a few additional fields for the visitors to provide the country name and state their headquarters is based out of.

Here are a few examples of basic lead routing (distribution) rules that are widely used by sales operations with SalesForce, Hubspot, Intercom and basically any other CRM as there’s not much difference between them in that regard.

Picture II - An example of standard lead routing (distribution) rules for a B2B software company

There are more complex routing rules, when multiple parameters make a rule. We’ve seen up to 5 different parameters blended in a routing rule. Here’s a quick example of a mixed lead routing rule.

Picture III - An example of a more complex lead routing (distribution) rule for a B2B software company


So it seems like we nailed it! We just built a few examples of lead routing rules that were designed to deliver the right leads to the right sales people. Seems like we’re ready to give these well thought-through items to our sales operations developers… but hold on a second. Ask yourself a question – why would your leads provide correct information about themselves and the business they represent? I can assure you that they don’t care about your needs and unless they are requesting pricing information or scheduling a one-to-one demo when they’re expecting a follow-up, the last thing they want from you is getting a phone call from your sales team.

Why would your leads provide correct information about themselves?

In fact, the more mandatory fields you put in front of your leads, the more the more garbage data you should expect. Remember, your leads don’t have any compelling reason to complete your lead capture forms accurately. Therefore, you can’t merely trust the data you collect and create business processes based on it without having a data quality process.


My experience tells that business executives outside marketing and sales functions find it hard to realize that the less fields you lead capture forms have, the better. They would not like my recommendation of leaving Full Name and Business Email Address fields untouched and erasing all others. Instead of asking your leads to provide more information about the business they work for, you should look at other options providing more accuracy and scalability. Consider implementing an automated data validation and data enrichment solution and setting up an in-house data quality team. We’ll talk more about the benefits of having an in-house data quality or data integrity departments in other articles.

Picture IV - Lead Data Enrichment Engine's integrated with a Marketing Automation Platform

Picture V - Lead Data Enrichment Engine's integrated with a CRM

Those two simple models map out a proper data quality process for every mature B2B software or SAAS company. Your leads submit their basic information such as full name and business email address and this data flows into either your marketing automation platform or CRM where the automated lead enrichment and validation engine gets you the data points your lead routing rules require. As the result, your data becomes more reliable and your start delivering leads to proper sales teams thus improving their productivity. They no longer need to re-assign those leads after they’ve had an initial conversation and discovered that their HQ location is actually in a state that doesn’t belong to their territory, etc.


The reason I mentioned that you’ll need a buy-in from other business executives outside of marketing and sales operations is because you’ll need to get the budget as data enrichment and email validation tools don’t come for free. In fact if budget’s not an issue, you should look at, but be prepared to pay a few hundred grand for access a year to the database, plus they’re charging extra if you want to provide access to multiple people within your company, not to mention consulting and integration fees. If you’re contemplating that you need more cost efficient alternatives, here’s a list of data points you absofreakinglutely need to make sure the vendors you’ll be talking to would be able to provide.

  • Company Name
  • Vertical/Industry
  • Number of Employees
  • Annual Revenue
  • Year founded
  • HQ Country
  • HQ State
  • HQ City
  • HQ ZIP/Postal Code
  • Website Address
  • Facebook URL
  • LinkedIn URL
  • Twitter URL

Also, before making a purchasing decision the best practice would be to run a trial data enrichment project where a vendor would process 1,000 leads and you’ll be able to see the match rate, in other words a percentage of the records that were enriched. Anything below 50% should be given a red light as you need to build a data quality process that would scale.

Before making a purchasing decision, run a trial data enrichment project for 1,000 leads.

Also a quick tip - an average employed person in the U.S. changes jobs every 2 years therefore you should avoid building your routing rules on the basis of the personal information. Not to mention that automated enrichment of personal information is prohibited by GDPR

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