Data quality: cost or useful investment?
More than ever, direct mail is proving its worth as an important communication tool.
It is a high-performance medium, with infinite personalization possibilities, that allows marketers to optimally develop their customer base.
Given the considerable costs involved, as a marketer you obviously have every interest in avoiding unnecessary expenditure. And that is precisely the merit of a consistent data quality strategy! Correcting movers addresses and eliminating duplicates has a direct impact.
Add to that avoiding missed sales because you can’t reach your customers, then investing in good data quality is totally a no-brainer!
Your data quality business case in six magic numbers
To calculate the return on your data quality investment, use six magic numbers:
The annual total number of mailings sent (number of customer records in your database x number of campaigns per year).
The mailing cost. For large mailers, the cost per piece is on average between 0.40€ and 0.55€.
The campaign conversion rate. Large mailers generate a conversion rate of 10 to 15 percent. So you can see why direct mail remains a popular medium!
The average spend per order or visit per customer. This amount is of course highly dependent on the sector. Do you have these figures per customer segment? Even better, because then you can refine the exercise!
The number of incorrect addresses due to movers.
Research by Black Tiger Belgium shows that an average Belgian customer file contains between seven and fourteen percent wrong addresses.
The number of duplicates in your customer database.
In order to measure the quality of your customer database, to work out this business case properly, Black Tiger Belgium will gladly submit your database to an audit. To measure is to know!
Business case – part 1 – Calculate your cost savings!
Step 1: calculate M – the total number of mailings sent: number of active clients x number of campaigns per year
Step 2: calculate C – the total mailing cost: M x average cost per copy
Step 3: calculate the cost of wrong addresses F: percentage of movers/wrong addresses/unaddressed persons x C
Step 4: calculate the cost of duplicates D: percentage of duplicates x C
Step 5: calculate the total cost of poor data quality TKD = F + D
Business case – part 2 – Recover lost revenue!
Wrong data also leads to not being able to reach (and therefore convert) the customers in question. Maybe these are a bunch of good customers, with a big impact on your campaign results!
Step 6: calculate the average annual campaign impact I: total number of mailings M x conversion rate x average spend
Step 7: calculate the potential lost revenue V = I x percentage of movers/wrong addresses/unaddressable people
Of course, this is a maximum! But you will be surprised of the size of this number anyway!
If you succeed in identifying your movers or wrong addresses, you can try to reach these contacts via other channels (e.g. via email or Facebook, but count on a lower conversion rate…). Or you can choose to clean up your file and purchase the correct addresses of movers.
Business case – part 3: Profit!
A permanently clean customer database for maximum return obviously requires an investment.
Calculate your profit (after deducting the cost of data quality) by adding up your cost savings ‘TKD’ and your lost estimated revenue ‘I’!
Black Tiger Belgium has made many such business cases with our clients. Ask for our help to develop yours, based on your business parameters and our audit of the quality of your customer base(s).
Contact us for a Data Quality audit