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The Little-Known Marketing Issue that’s Secretly Killing Your Sales (And How to Fix It)

Not long ago, “Big Data” was all the rage. The race was on to collect as much information about people as possible – creating a giant, looming cloud of detail that was nearly impossible to sift through and a challenge (at best) to market to. Today, we have more tools than ever to wrangle that information and use it to present clear, compelling reasons for customers to want what we’re offering.

But there’s still a lingering problem.

As marketers, optimizers and improvers, we focus a great deal on the performance of our campaigns. We track open rates, click-throughs and conversion rates without giving a second thought to where that data comes from.

And that lack of attention is costing us – big time.

What Exactly Is Bad Data?

Information collected from prospects usually isn’t wrong when you’re first connecting with them. But over time, people move up (or move on) in companies, change email addresses, merge with other companies or segment their division into an entirely separate entity.

And it happens more often than we realize.

percentsIs Bad Data Really Worth Worrying About?

You may think that an incorrect email address or a wrong company contact here and there wouldn’t really make an impact – especially if you’re getting solid results from your existing campaigns. But for every lead that enters your funnel, there’s always the possibility that the information is changing quicker than your CRM database can keep up.

A study by DiscoverOrg found that sales and marketing departments lose approximately 550 hours and as much as $32,000 per sales rep from using bad data.


But putting a price tag on the number of sales lost from bad data isn’t just about the money. It’s about the time lost that could be better spent working on engaging leads rather than chasing down lukewarm non-responders. It’s about that burst in morale and spirit that comes from closing a sale when everything you do is right on target. It’s about maximizing efficiency and productivity on every level.

And at the heart of it all is the very data you’re collecting.

The Bad Data Snowball Effect

As more time passes, the effect of bad data seems to snowball. Not only is time wasted chasing incorrect or outdated data, but information (especially online) becomes outdated very quickly.


The last thing you want is a database full of duds. But by the same token, incorrect or outdated information caused by the sheer vastness of data out there can also be improved by it – if you know where to look and how to keep your existing CRM data squeaky clean.

Getting Everyone On Board

The good news is, bad data doesn’t have to drag your conversion rate and closing numbers down. Now, more than ever, marketers are coordinating their efforts across multiple channels, which means the need for accurate data is one of their primary focuses.

That means that while the sales department likely has its own automation system for follow-up, marketing also needs to have its finger on the pulse of this information. Both parties should ideally be able to access, update and reference this information to form a complete, cohesive “big picture” of the data.

Even bringing customer or technical support into the fold is a smart idea. If service calls show that a certain problem is common but easy to fix, sales can break down that resistance early on, while marketing can pinpoint a way to introduce more customers to the solution based on its ease of use. All of these groups working in tandem helps create a more concentrated, goal-focused, customer-centered unit – and customers appreciate that kind of familiarity.

Practicing Good Data Hygiene

Inaccurate information can not only affect sales and productivity, but credibility as well. Good data hygiene means taking the time to clean up, verify and organize data so that common issues like duplicates, mismatches and missing elements no longer plague the system.

But in addition to scrubbing your CRM, it’s also a good idea to look beyond the details you’ve collected already. Can you connect social media usernames or accounts with these leads? What about mobile device information? If you’re just now opening the floodgates to sharing data between departments, are there any areas where information can be appended or merged so that you have a more complete picture of the customer?

Of course there is no shortage of both free and paid tools to help ensure optimal data cleanliness, many of which are already part of existing CRM software (like Salesforce) or other analytical tools. Oftentimes, companies will hire dedicated data-cleaning teams whose sole purpose is to keep records up to date and relatively error-free.


Even the most accurate information will change over time

Even if you’re doing it yourself or with a small team, it’s easy to look at waves of bad data and feel like you’re drowning in inaccuracies. It’s no small task to not only correct bad data but keep it fresh and up to date. Creating a sort of “data plan” can help you eat that elephant one bite at a time. In creating such a plan, ask yourself the following questions:

  • Who has access to what information? Not only are there privacy and security policies to keep in mind, but also the fragmented nature of the data collection to begin with. Getting everyone on the same page and making sure the right people have access to the right information is crucial to making the most out of every campaign and strategy.
  • How do we measure data quality? – You already know fields like name, phone and email address have to be accurate, but how else can you measure data quality? Knowledgent has an insightful white-paper on the topic, including analyzing key points that can degrade the quality of the information you collect, like consistency, timeliness and uniqueness.
  • What path does our data take and how can we make it better? – Let’s say a customer in your database has just switched jobs. In addition to putting their new position in your CRM, consider things like whether or not they are still a key decision maker in their new role, and if not – who is. The last thing you want to do is compound the time lost by sales staff in chasing down referrals who don’t have the authority to move forward.
  • What goals can we set to make data cleansing more valuable? Turning bad data into good data is no small job. Taking it step by step by focusing on the high ROI targets will keep everyone engaged and motivated to improve. Set real, measurable, attainable goals and focus on the journey instead of the destination.

By putting these steps into practice, you’ll not only walk away with a squeaky-clean database, but improve your business credibility, resonate with your target audience, increase sales productivity and build stronger relationships with your customers at every stage in your lead generation funnel.

Have you been the victim of bad data? How has it affected your business? Which tools do you use to keep information current? Share your insights with us in the comments below.

About the Author: Sherice Jacob helps business owners improve website design and increase conversion rates through compelling copywriting, user-friendly design and smart analytics analysis. Learn more at and download your free web copy tune-up and conversion checklist today!

  1. Silvio Porcellana Jan 19, 2016 at 12:08 pm

    I really like the “cycle” mentality. All too often reps – which rarely have a good relationship with CRM’s… – think the lead is inscribed in stone once it’s entered in the system. This is absolutely not the case and monitoring, fixing and updating data as soon as it changes can prevent huge losses down the road – when the bounce rate of your emails skyrockets and you don’t know why…

    Thanks for this!

  2. It’s a great research done by you. Every second huge amount of data is generating and if you want the accurate data to analyze then there should be some tool which clears the bad data in the back end.

    And for any organization to be successful Sales & Marketing department should run parallely and should analyze the correct data and remove bad data from their CRM.

  3. Any metrics to support impacts on deliverability and inboxing?


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