Your reputation and your ability to communicate effectively are important, and whether you are using direct mail, email or personalized URLs, your data is the underlying foundation.
In today’s world we see people with a broad range of skill sets setting up and managing marketing data. This, in turn, leads to dramatic differences in the quality and reliability of data out there. For some, what follows may be “motherhood and apple pie”, but for others, we hope that these tips might help to establish solid and dependable marketing data.
Before looking at what we can do to ensure the quality of our data, l think it is important to look at the consequences of unreliable data, so here are some of the challenges we might face:
- Sending the wrong messages to particular groups
- Sending incorrect information to customers and prospects
- Missing key customers and prospects
- Impersonal communications
- Embarrassing personalized substitutions
- Delayed delivery of mail
- Increased costs
Not only can these problems be a major source of embarrassment, they can also result in losing customers. However, as we will show, they can be avoided through good planning, good execution and ongoing commitment.
The following is a list of tips you can use to establish and maintain clean useable data. Each of these will be discussed further under separate headings:
- Start with or update to a good basic structure
- Establish and assign responsibilities for strategic information
- Use edits where possible
- Get the right data in the right fields
- Avoid apathy
- Start with or update to a good basic structure
Good data structure begins with a place for everything and from there we hope that everything is in its place. However, we see a lot of data files where key fields are missing which can result in a lack of flexibility and often increase costs. While starting with a good structure is your best bet, I should also note that while some existing structures are easily modified, this is not always the case for some older systems that offer limited flexibility in this area.
A very basic name and address file would appear as follows:
- Postal Code
There is no doubt that this structure could get a piece of mail delivered, but what if you wanted to send a personalized letter, note or email? Would you like to see “Dear Angela Osborne”? Even if you do split your contact data into first name and last name, it is sometimes a good idea to include a separate greeting field. Again, it just gives you more flexibility, especially in cases where you might be dealing with two or more first names in the greeting (e.g. “Nancy and Albert”).
Before continuing I would like to share some data we received a while ago. I did substitute different names so that we would not be showing you live data. Without exaggeration, this is how the contact name fields appeared:
- Saunders, Bill
- Smith, Sally and Robert
- Johnson/Albert and Julia
- West David
- ABC Enterprises/Donaldson,Bill
Interestingly, the client wants to send out personalized letters with proper greetings. While the data can be restructured to make it useable, a bit of basic planning could have avoided the associated costs.
Here are a few other suggestions you might consider:
1. Even if your primary business is consumer based, it does not hurt to add a company name field as, inevitably, you may sell to a business or some other type of organization. Having company information on your file doesn’t cost you anything and it avoids trying to jam company information into some other inappropriate field.
2. You may need to include a department name when entering company data, plus there are some very large address out there, so use a couple of fields for both street and company name information. Again, a bit of planning ahead precludes you having to wedge data into fields where it does not belong. Further, entering additional company name data into your address fields can affect your address accuracy, cost you money, and in some cases, delay delivery.
3. As you will normally want to print company and address fields on mailing pieces, try to keep these field values within a reasonable length of 40 to 50 characters. As suggested above, it is okay to have a couple of fields for both your company name and street information, just keep an eye on the lengths.
- Establish and assign responsibilities for srategic information
Strategic information includes data such as status (e.g. customer or prospect), product or service interests, industry types, buying patterns, usage patterns etc. Your list of strategic data fields (or relational datasets) can be as long as you like. Provided it is kept up to date, this information is a powerful base for targeted marketing, allowing you to tailor specific messages for different groups.
As powerful as targeted marketing techniques are, with strategic data also comes responsibility. Once you have defined what information will be maintained, responsibly for the integrity of the data should also be assigned to an individual or a functional area. We all know about “good intentions” and the proverbial “road”, and without assigning responsibility for data, it can deteriorate very quickly.
Before leaving this point I would like to demonstrate how these problems manifest themselves in the real world. I had occasion to work on a system a while ago where data was originating from three different external sources. Although the values were ostensibly the same for each source, somehow there were subtle differences in how they were being recorded. For example:
- 1 to 3
As you can see, to the human eye, they appear to be the same, but they would be considered entirely different by a computer and could not be used, as received, for strategic targeting.
As this was strategic marketing data, our job was to fix it, which we did, by establishing the desired values for various fields and then mapping them accordingly to common values. Simple edit values, as discussed below, could have avoided this problem and saved money.
- Use edits where possible
Edits allow you to control what values can be entered for specific fields and we can also use edit masks to ensure that data is entered in a specific format (e.g. A9A 9A9 for postal codes).
In its simplest form, an example of a field edit could be establishing allowable values for Industry Type, such as: SRV for Service, EDU for Education and MFG for Manufacturer. If someone attempted to enter MAN for Manufacturer, the entry would be rejected. There are also logic edits that look at a value and assess it based on a variety of conditions. It is beyond the scope of this article to look at all of the various types of edits you might employ. However, they are a powerful way to help you ensure the integrity of certain fields, and if you are not already using edits, they are worthy of further research.
- Get the right data in the right feld
It is critically important that we enter the right data into the right fields and it is equally important to ensure that all fields are updated, because missing key data can also affect selections for target segments.
When we looked at the contact name, company name and address fields above, we mentioned how you can be forced to enter the wrong data into a field if you do not have a data structure that accommodates the information. Unfortunately, the challenge can go beyond this and, if you are not using edits, you could also end up entering strategic data into the wrong fields.
Here are just some of the things that might go wrong when we don’t have the right data in the right fields.
1. If your messages hinge on whether someone is a customer or prospect, and you are not keeping this key information up to date, you might be telling someone who just bought $50,000 worth of products or services from you about how much you want them as a new customer – embarrassing!
2. If you want to target a particular segment, as in the example of MFG (Manufacturer) above, and you did a select on MFG, you would miss those with values of MAN, MANUF or nothing at all in the Industry Type field – dreadful if you just missed sending a special announcement to one of your best customers!
3. If we happened to place street data into a company name field, and we want to include the company name in a personalized letter, email or pURL, we could see something like, “We hope that we might be able to add 135-14 West Albion Street to our list of satisfied customers” – again, very embarrassing.
5. Avoid apathy
We all tend to get excited about something new and new systems are no exception. Having done my due diligence as a systems analyst a few years back, I always enjoyed writing user documentation and conducting user training for new systems. There was always an eagerness to learn and get this new “puppy” on the road. But, as time passes and line areas experience a bit of turnover, the lustre tends to wear off and apathy can set in. If the keenness leaves and people start to cut corners, data challenges can start to creep in. As good as some edits are, creative workarounds can also become a challenge and add to the dilemma.
Strategic marketing is an exciting discipline and being part of the team should be a rewarding experience. At the same time, it is important to provide the same levels of system training that you provide at the outset for new people that might come on board to administer or work with your marketing data. If you keep it fresh and the programs are delivering, apathy should not become a problem.
As a final note on this subject, data is critically important as it not only helps to increase sales, but also represents your corporate image. As such, managers must stay on top of it to ensure its integrity and that it continues to be used effectively.
Personalized URLs, highly targeted communications, powerful email and highly creative direct mail make today’s direct marketing more exciting than ever. However, as we noted at the beginning of this article, it all rests on the foundation of your data, and good usable data is critically important to the success of your marketing programs. To this end, we hope that one or more of the ideas presented above can help you to establish and maintain clean and dependable marketing data.