CRM Maintenance 101: How Dirty Is Your Data?

CRM Maintenance is becoming ever more important. If you don’t actively cleanse and update your data 70% of your database could be inaccurate after just one year.

Sound too high?

In 2016, the UK saw a record high in business formation; 650,000 new businesses were started last year, over 40,000 more than in 2015. In 5 years time, around half of those businesses will no longer exist. With more people job hopping and freelancing – your contacts are unlikely to stay in one place for long.

This environment presents a serious challenge for any company’s CRM and contact lists. For a typical B2B company, between 2 and 5 percent of company data decays each month.

Growthonics has worked with over 400 companies, including with helping clients cleanse their CRM databases, effective data entry and data discovery. We have experience across the board when it comes to database best practice. So we have compiled a few articles to discuss the dos and the don’ts of storing data.

With the upcoming changes to regulation in May – I am of course talking about the infamous GDPR – the ‘I’ll do it later’ and ‘it’ll be fine’ attitudes no longer fly. You have to be on top of who you are storing as a contact – and for how long.W

A few key terms

Before we begin, in the interest of avoiding sales jargon and buzzword gibberish, let’s iron out a few key terms.

  • ‘Data erosion’ refers to the process of stored data becoming out of date or irrelevant for sales and marketing purposes.
  • ‘Course’ or ‘dirty data’ is data that is either now irrelevant for whatever reason – companies move or go bankrupt, email conventions change, phones are lost, people move etc. – or has been entered incorrectly or incompletely.
  • ‘Data scrubbing’ or ‘CRM cleansing’ counteracts these inaccuracies by removing dead leads, correcting typos, and updating lead information.
  • ‘Data discovery’ is the process of finding replacements for previous contacts and replenishing your CRM database once the dead wood has been removed.

How Dirty is Your Data?

60% of companies rate the overall health of their data as ‘unreliable’ – what would you rate yours?

SiriusDecisions found that the average B2B database is 25 percent inaccurate at any given time. That is every fourth contact in your database right now.

Research from Experian Data Quality has shown that inaccurate data has a direct impact on the bottom line of 88% of companies. Paying your staff to pursue dead leads, and pouring money into resources and marketing spend when your data is inaccurate, is an expensive mistake. One that costs the average company loses on average 12% of its revenue.  According to the Data Warehousing Institute, poor data quality costs American businesses up to 600 billion dollars every year.

Bad data doesn’t just cost you money – it also can cost your brand credibility. Out-of-date or misplaced messaging worsens your customer’s experience – 28% of companies Experian surveyed who have experienced problems delivering emails also reported that customer service suffered as a result. A further 21% experienced reputational damage as bad data leads to inaccurate targeting and prospects do not like to be hit with irrelevant messaging.

So… How Dirty Is Your Data?

We have compiled a list of tell-tale signs that your data has eroded.

Do any of these points apply to you?

Here is a little more context to each for anyone newer to email marketing or in need of a reminder:

  • Your bounce rate is higher than 10%. An email bouncing indicates that the account is no longer in use or the address has been entered incorrectly – a definite sign of you need to work on your CRM.
  • You duplicate rate is over 1% on any campaign. Duplicates are a sign of sloppy data entry and an out of date CRM. Your duplicate rate should be 0.
  • Your unsubscribe rate is over 2%. People unsubscribe when messaging is generic or irrelevant – so if your messaging is going out to the wrong contacts, like sending prospecting emails out to current clients for instance. Other indicators are a lower open rate and a lower reply rate, but bear in mind that any of these could also be an indicator of poor content and strategy.

What Can You Do To Cleanse Your CRM?

1. Deal with it internally.

You could set up teams internally to handle regularly checking through your CRM data, with the help of data scrubbing automotive tools (see below). The size of the team, and the cost of this investment will vary depending on how large your CRM database is. For most companies, handling regular cleansing and health checks internally is time-consuming and expensive.

2. Tools and Automation.

There is a wide variety of tools that you can use to help maintain your CRM’s health, some that come as part of (or add-ons to) some of the most prominent CRM systems like Salesforce. These tools can help flag multiple data quality issues, however for the purpose of data erosion the benefit of these tools is limited as they can only flag bounces, not replace them with viable contacts. This means they cannot effectively deal with the issue of employees having left the company and suggesting replacements.

3. Outsource the work.

CRM cleansing and data discovery to replace old contacts is time-consuming and expensive to handle in-house. Sourcing replacement contacts will involve hours of time, so many of Taskeater’s clients have opted to outsource this work. Offshore teams are able to deliver high quality leads to replace old contacts, as well as sift through CRM data to find inaccuracies and duplicates. Generally, this is a more cost-effective solution than dealing with these issues in-house.

A final word…

Growthonics offers CRM cleansing and data discovery services to B2B companies of all sizes, all over the world. We guarantee complete confidentiality and security – any data we process will not be stored on a centralised database and will not be sold on. We remove leads you no longer need and replace them with active contacts with accurate contact details. We also help you become GDPR ready by tagging your data sources and replacing personal data with corporate data.

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Abu Hena Chowdhury

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