Posted: October 17, 2017
Categorised in: Direct Mail
To create a successful direct mail marketing campaign, you need data. The problem with data requests is that they are often vague. In other words, the terms used to define a data profile can have several other meanings, or be interpreted in a different way to how another identifies the persona. In turn, this can cause problems for a direct mail company, using the data for direct mail design and campaigns. Likewise, it can affect clients and data suppliers.
Data Case Study
To analyse the importance of data and how to define the best data for your direct mail, we can look at an example. The words: “I want data for all the marketing decision makers from Liverpool, that come from the best socio-economic areas” seems abundantly clear. However, we can examine this in closer detail.
What is the definition of data?
Data for direct mail marketing campaign management can take many forms; emails, address, phone numbers, census data, open data, data without mailing preference service (MPS) flags.
What is the definition of ‘marketing’ in this data context?
Does a sales contact count as a marketing contact? How about a fresh out of University junior who has a budget of £100? Or the Chief Marketing Officer of Sage who manages the marketing teams, and who holds ultimate accountability but not the responsibility for everyday spending?
What is the definition of ‘decision maker’ when it comes to collecting data?
‘Decision maker’ means different things to different people, when it comes to collecting data for direct mail. A salesperson would be looking for a decision maker who had BANT (Budget, Authority, the Need, and the Time) to say yes to their sales pitch. However, to a Managing Director, ‘decision maker’ might mean the person they can network with to conclude deals at the Board level.
What is the definition of ‘Liverpool’ in the case study?
Geography definitions are a minefield when it comes to data. You must first find out what is being requested and the actual city area. Alternatively, could it be the geographical area the city sits within or the area defined by the ‘L’ postcode.
What is the definition of ‘socio-economic areas’?
There is the tendency to assume that everyone is working within the same framework, but most major data suppliers have their own proprietary system. There’s now a widely accepted ‘open data’ format in addition to the paid-for structures. While there will be overlap to each data providers system, it can’t be guaranteed that their methods of calculating socio-economic groups will be the same or even remotely similar to each other. In simple words, you must tell your ‘data provider’ exactly what you want. In addition, vague data requests have an unfortunate side-effect on the actual people who ‘pull’ the data itself. It will have a ‘knock-on’ effect of the accuracy of your data and, if so, that’s a waste of time and money for your business.
Top tips for collecting direct mail data
It’s clear to see that issues with data arise with accuracy. We have outlined the best tips to ensure your data request exceeds your direct mail marketing expectations.
1) Ensure the data is correct
It may seem obvious, but your data must be correct. The direct mail company providing you with marketing campaigns can only work with the data provided. Your customer profile must be as accurate as possible, with plenty of testing beforehand. Data providers are exactly that; providers. Advice on customer profiling is not, typically, part of their role and to make sure your marketing campaign management is at its finest – your data must be clear and accurate.
2) Be hyper-accurate
To follow on from the previous point, make sure that your brief provides the most semantically accurate parameters for your data request. By doing so, you’ll limit any potential issues that might cause delays in the ‘downstream’ process.
Ensure your Account Manager has no questions regarding your brief. This one simple act will not guarantee smooth and accurate provision of data, but it will put the ball firmly in the court of the provider. They will have to provide exactly what you asked for on time, and to the standards, you have defined.
The more accurate the data request provided – assuming the profiling of the customer is correct in the first place – the better the response rate and the better the return on investment will ultimately be from the data provided. You can see the stats if direct mail is produced correctly, with clear data, in our Powerful Direct Mail Statistics article.
If you need help in defining your customer profile or requesting data, get in touch with one of our team today.