You know you have a CRM problem when you srtat hearing comeents like: “Wrong phone number”, “The company was acquired”, “Wrong title”, “I have duplicates”, “The data is old”, “The emails don’t work”, “My CRM data sucks”, “I just called someone who’s been dead for a year”…
Are there solutions to these problems? Yes, however, here’s a deeper understanding of why the problem occurs. Many good vendors exist to solve the problems listed above. I want to arm you with a deeper insight: the why.
If you understand the why, you will be able to:
- Have a deeper understanding to the nature of the problem
- Remove unrealistic expectations (solve the problem, don’t chase a rainbow)
- Define best practices to minimize bad data
- Be informed when choosing a vendor (flashy interface does not solve the problem)
- Understand how your CRM decisions effect CRM data
- Help you be an advocate for change management within your organization
- Make you a more informed client (some vendors will like this, others will not)
So what is the why?
Short answer: Contact data decays
If you have a short attention span, if you are brilliant, or if you have limited reading time, we are done here. That’s all you need (and you know what I am going to say in the long answer). Thanks for reading.
First, let’s establish a baseline from the US Department of Labor.
The national average tenure across all jobs in the US is 54 months. That breaks down to 1.85% per month of job attrition. For high-demand IT workers, the tenure is shorter with 3% monthly job attrition rate. The rate for Silicon Valley start-ups is almost ridiculous with the average tenure being just over a year, according to several Venture Capital blogs (not from DOL so take it as an extreme example).
A full year of data decay: Base factors
A month at a glance does not show the full picture when factored across an entire year. Look at the picture across a year’s time. When reviewing an entire year, data will decay at about 12%. However, that does not take into account many additional factors including:
- Change in title, promotion
- Change in working location
- Change of phone number
- Add mobile phone number
- Change of department
- Change of area code
- Change of email format
- Change in email domain
- Change in company name
- Change in company website
- Merger or acquisition
While I did my best to outline all the factors, there are some that I probably missed. What I wanted to show is a picture of why data decays. For the past 10 years, I’ve been immersed in data, the acquisition of data, and the analysis of data. From this experience, I know that data decays somewhere in the vicinity of 2.8% to 5.5% per month. This is based on:
- Hand verified data-sets that I’ve been building and maintaining for four years
- Poll-based responses from five years of live training webinars, and
- General industry sentiment.
When adding in all factors, the picture changes significantly.
A full year of data decay: All factors
Don’t make the “additive mistake.” 5.5% decay per month does not equal 66% over 12 months (it’s actually 36%). You must add each month and its data age and then factor in the average data loss across a year. It’s still not a pretty picture. In 2011-2012, the numbers were sitting at the high end of the continuum, somewhere in the 5 – 5.5% range. This means that you can expect data decay to be sitting somewhere around 36% a year.
The implications for CRM data health
So what is the health status of your CRM data? Start by finding your CRM Data Update Cycle. This is how often you go through a CRM full data update. Next, based on what you know about the sector you sell into, pick a Monthly CRM Data Decay Rate. As a guideline, in 2011-2012 the average is 4.5-5.5%.
Based on the 2011-2012 numbers, to stay under the 10% threshold, your CRM should be refreshed every 60-90 days.
“Hold on Donato,” I get this statement often, “I’m updating contact information in my CRM all year long.” My response is a question: What percent of all accounts in your CRM do you connect with each year and update their contact info? Typically the response is somewhere in the 15-20% range. Again, you must apply the data decay principal to data updated over a year time. For example, if you connect with 1,200 accounts per year, or 100 per month, then at the end of the year, the first month’s data is 11 months old, or somewhere in the neighborhood of 33% outdated. If you are doing a fully updating contact information (name, title, email, phone, company URL company phone, etc.), then each time you connect with an account, you can give yourself a 5% data health increase.
This begs a question: Who should be in charge of updating CRM contact data? If you expect sales to do it, I have a bridge to sell you in New York. My answer is Marketing or IT, based on how your organization is structured.
Where does this leave us? At this point you should have a solid understanding of the why behind data decay. In addition, you should have a more accurate understanding of your CRM Data Health. Lastly, you should want to take action. In this blog, I want to leave it as pure educational vs recommend vendors. Vendors come and go, the percents of data decay may fluctuate, but the concepts should hold true for some time.
Learn more about data decay in this infographic.
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