One accepted universal fact about data is that like many perishable things in world data too gets bad over time. There are many reasons why data decays - people change organizations, get newer designations, relocate to new places, assume new roles or in case of changing company structures through mergers/acquisitions or restructuring.
The rate of decay is variable and depends on your target addressable market (TAM), one way to access data decay is by looking at the employee attrition rate (or turnover rate) of different industries present in your TAM.
US companies had an average annual turnover rate of 22%, this means that an average of 1.83% turnover in a month. Another anecdote pointing to severity of decay is an email marketing study of 200 million emails, though inconclusive this study found out bounce rate between 5-15%.
Keeping these figures of data decay in mind, it’s imperative to make a strategy to be relevant. It is to be checked how data decay impacts overall marketing strategy of the company. Below are few sample calculations that would help one understand dollars lost due to bad data.
Cost of data management, reputation, & replacement
Suppose you have 1,000,000 records in your CRM, if you go out in market to purchase one such records it would cost you $1. Therefore the total cost of your data is $1 x 1,000,000 = $ 1,000,000.
If kept unchecked, there are various issues that creep in, keeping just US company employee turnover rate as reference, this means about 22% of data becomes bad annually.
This means out of 1,000,000 records 220,000 are not usable after one year.
Bad data not only needs replacement ($1 replacement cost) but also is associated with a reputation cost & storage cost. Let’s assume $0.48 & $0. 15 as reputation cost & storage cost. This mean total cost of each bad record is $1.63 ($1+$0.48+$0.15).
Now multiplying each bad record cost with 220,000 bad records gives out a whopping dirty data cost of $1.63 x 220,000 = $358,600.
So far we just spoke about what is cost of dirty data, in this section we would go one step ahead & talk about impact of dirty data on your sales pipeline assuming 22% annual data decay rate.
We again assume you have 1,000,000 records in your CRM, suppose out of these 20% constitute your ideal customer profiles (ICPs) who have high probability of conversion. Here is sample sales funnel:
Revenue loss due to data decay:
Here is the link to the calculator.
Total cost of data decay
With conservative rate of just 22% annual data decay rate you end up losing approximately: $35,200,000 + $358,600 = $35,558,600 which is 22.2% of your annual revenue.
Data decay is a reality & cost of dirty data is huge, you have to look for a solution that directly syncs with your CRM, MA & keeps data up-to-date. Zylotech B2B Self Learning CDP with its always on dynamic data management feature enables data updation on the fly whenever new information is available of your TAM accounts across hierarchies and relevant contacts within them.