6 Essential Tactics for Culling Garbage Data from Your CRM - Maximizer CRM

6 Essential Tactics for Culling Garbage Data from Your CRM

BY Jan Carter - Head of Product & Development
April 5, 2018

The acid observation, “garbage in, garbage out” is as true 20 years ago as it is today. Whether your database runs on your server, a third-party cloud service – or an immutable block chain ledger – your contact information is only as good as what you put in. And now with new innovations promising to supercharge CRM, getting rid of inaccurate, outdated and redundant data has never been more important to businesses who want to keep their competitive edge.

The use of AI for CRM, for example, is slated to expand rapidly, generating up to $1.1 trillion in new revenue by 2021. Those businesses that stand to reap the biggest advantages will be those who successfully apply innovations like machine learning and predictive reasoning towards businesses processes such as sales automation. No matter how sophisticated the program, however, an AI trained on bad data will give your team useless advice, and you may not even realize the damage until it’s too late.

Getting your CRM innovation-ready ultimately requires being up to speed with best data management practices. And since cleansing data can be tedious, time-consuming work, it pays bundles to know where you can trim the fat in your data handling processes. Here are 6 essential tactics we find help our customers organize their data while saving time.

  1.   Define your critical information – and remove the deadwood

Data that serves no purpose just sits around in your interface, creating visual clutter that distracts your team while making vital data points harder to isolate.

With data capture, parsimony is the rule: you want to ensure your team only captures what they need for each stage of the customer journey. You’ll want to take every extraneous data-point off the map so your staff concentrate on what’s relevant in a given situation.

For example: how relevant are data points like company address or revenue – do you actually use that data to define customer segments? Or will first name, last name, email and phone suffice for the product they are interested in?

  1.   Kill the dupes

Likewise, duplicate entries serve to clutter up your Address Book, confusing your team, frustrating your ability to keep entries up to date, and disrupting your ability to forecast accurately.

Kill duplicates using your CRM’s built-in data management tools. You’ll want to be able to quickly pinpoint redundant entries and eliminate them in a few clicks, to keep your address book as clean and tidy as possible.

  1.      Segment your customers

Another way to help organize your database is to segment your customers by categories like age, location and gender; industry, buying frequency, and more. By segmenting your customers, not only will you improve your information management, you’ll also improve your ability to assess leads and pipeline performance, and improve your customer outreach. As discussed in #1, the idea is to only collect what you need.

  1.   Centralize, centralize, centralize

There’s nothing worse for team alignment than having their data squirreled away in separate solutions. Bringing information together helps build centralized intelligence on your customer preferences, history and status. But there are more than one way to achieve this end – and not all of them are appropriate for your business.

For example, if you’ve got a relatively small team, it may be simple to transition them onto a single platform by buying new CRM licenses and training them up. If you’ve got multiple departments, each used to working on their own apps, then integrations are another rock-solid way to share information on leads, payment history, campaign data and more.

But unless your vendor has pre-built integrations with your business-critical apps, you’re going to have to hire costly and time-consuming third-party consultants to build these integrations yourself. Sometimes, these can be well-worth the effort. In other situations, it’s cheaper to simply hire someone to do data entry between systems.

  1.   Create a “universal customer ID”

Email addresses work fine as a unique ID -- until you step outside of an ecommerce situation. Another alternative to achieve centralization is what data architects call a “universal customer ID”. This entails tagging customers with a unique number – like a SIN – ideally stored in a centralized database. This help you establish data consistency, while enabling you to better track customers across your different channels, products and departments – essential if you plan to run bigger analytics projects on your entire business down the road.

  1.   Use the audit log feature

Finally, no matter how good your data capture, no dataset is bullet-proof. You’ll want to be constantly testing it for flaws and when you find a leak, immediately plug its source. This could be a staff member who needs a little more coaching on your data entry policies -- or a software bug. In either case, you’ll want audit logs you can easily search and filter to quickly pinpoint problem areas.


Have any data management tips or tricks that have worked wonders for you? We want to know! Share with us on Twitter or LinkedIn.

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