…or Sonar: a system for the many, not the few
When you say “geo-demographic profiling system” it sounds rather fancy. In fact, I would say it sounds really overwhelming – at least, it did when Graham first mentioned it to me. Only experts could get their heads around that!
However, it isn’t that hard to understand. That is, it isn’t something to be dismissed for just the ‘few’ out there who have a brain for data and analytics. If I, an English Literature graduate, can get a hold of what Sonar is and does, then I am confident Sonar is a system that can be used by ‘the many’ out there who are seeking to market in a unique and effective way.
What is Sonar?
First things first, Sonar is a geo-demographic profiling system (as said above), created by David Griffiths. Simply, this means it sorts out the population into groups dependant on certain characteristics.
How does it work?
As a business, you may have a file of customers which include your recent customers, perhaps lapsed customers and those who you have your eye on as potential customers.
For Sonar to work, you need to have postcodes within this file. Postcodes, as I have learnt, are extremely important here. With your file, Sonar will generate groups dependant on two key factors: Lifestage and Affluence. These groups will be assigned a three-digit alphanumerical code. For example:
Now, the first digit indicates the customers Lifestage. There are 6 Lifestage groups and they are quite broad.
A – Young Singles
B – Young Families
C – Families
D – Mature Families
E – Empty Nesters
F – Retired
The second category is how affluent they are. There are 4 groups – called quartiles – which customers are split into.
- Less Comfortable
Just to nail this down, here’s Sophie. If she was a customer of Finely Fettled, let’s say, we might run her through Sonar using her postcode. If we received the code A24, we would know Sophie is a comfortable young single customer. That would be her customer profile.
However, something I got stuck on is the third digit. If there are only two groups used to categorise customers, what is the use of ‘4’ in Sophie’s profile, or even the ‘1’ in the example further above.
Well, this is just a further category to refine how comfortable or affluent or struggling the customer might be. Sophie, for instance, is comfortable but she isn’t as comfortable as a customer who is ranked A21. It’s just a further refining of the groups for comparison.
The codes that Sonar creates can then be used to identify and target your ideal customer (this will be covered a little more, later on).
Top ups, look-a-likes and the index
Like any software or system, there’s always some jargon to go with it. As someone who was and is still relatively new to Sonar, I found the jargon a little confusing. Hang on in there while I try to explain…
– Top Ups
Top Up is a funny name, as it can be slightly misleading in the sense it might remind you of a “top up” of a drink. However, in targeted-marketing terms, a Top Up is about having a small cluster of current customers in a postcode.
For example, imagine a postcode in which there are 19 houses; 4 of those properties belong to your current customers.
Regardless of Sonar’s profiling, if there is a cluster of present clients or customers, it is a good bet to target those areas with your marketing.
As Graham likes to say:
“Birds of a feather flock together!”
It’s good to target these postcodes because it is highly likely that those living near your customers are going to be similar. Therefore, there are good prospects for further business within the area; said using targeted-marketing jargon, there is the potential for a further penetration of a postcode where services/products are already being used.
As a result, you are ‘topping up’ the postcode with, in the case of the example above, 15 prospects.
Now, the idea of Top Ups are not really Sonar-related here, but come with the targeted-marketing territory. However, it’s not wise to just rely on Top Ups, and this is where Sonar comes in to generate look-a-likes.
When Graham and myself were discussing Sonar, he asked me:
“What is the point of looking for prospect clients or customers in a postcode where there aren’t any current customers?”
As a business, there may seem quite a risk to send direct mail to postcodes you have no clue about. You don’t know if they fit into your ideal client profile and therefore doing so would cost, with the risk of the cost not being worth it. In short, using new and unknown postcodes does not obviously advance sales.
Here is where Sonar comes in…
I’ve discussed how Sonar generates a code using a business’ customer file. When Sonar generates a customer profile, your current customer may be grouped in E2. Within the E2s, there may be other people living in different postcodes. These would be called Look-a-Likes.
Here is a visual example:
This house belongs to a customer of a business in a postcode in Derby. When run through Sonar, it fell into the E2 category – empty nesters, comfortable.
This house, also in Derby, received the same Sonar profile category – E2.
However, it belongs in a postcode where there are currently no customers or clients. Therefore, the property above is called a Look-a-Like.
These Look-a-Likes, in addition with the Top Ups, are then ranked from most to least like your ideal customer. The way in which these postcodes are ranked will be explained below.
– The index
To be able to rank the postcodes (and produce an index), there’s some maths involved. Once Sonar has profiled clients (both current and potential), there are two percentages that are dealt with.
The first percentage shows the concentration of a certain Sonar profile within the UK. For instance, within the population, 4.1% are profiled as F1, retired affluent. Within, let’s say a charity’s file of customers, 18.22% of their donors are profiled as F1.
The maths here involves dividing the charity’s percentage by the national percentage: here that would be 18.22 x 4.1. Times this outcome by 100 and we get 444.3.
This number is called the index and it shows the degree to which the Sonar profile category is most like the charity’s best clients/donors. In other words, the higher the index, the more likely that particular profile is going to be an ideal customer, client or donor (depending on the business or charity). This is visually represented by a graph which is demonstrated to the right.
As you can see here, the F1s extend beyond the 300 mark.
The index is used to rank different Sonar groups or postcodes to identify where the greatest concentration of customers are.
The categories that are most like a customer file will rank at the top so that, at the bottom, you’ll have those who are least likely to engage with your services/product.
So what? Mailing, Sonar and Finely Fettled
You might be thinking this is all very interesting but not really relevant. Wrong. This is incredibly relevant to marketing strategy and direct mail.
With this ranking information, Finely Fettled can go down the ranking until we meet your mailing volume. If your mailing volume was 10,000, and there were 9000 F1s, we would go to the next highest index number (in yellow) and use that category to bump up the numbers and so and so forth.
By doing this, Finely Fettled can help refine your direct mail targeting. Using Sonar, we can ensure that your target-marketing is refined to truly target those who are relevant to your services and products. With direct targeting using Sonar, you will be more efficient and more successful in your marketing.
It is important to note that you can also use various other attributes to further hone these categories and make your profile of potential customers much tighter and specific.
Address-Only Target Marketing
Here at Finely Fettled, we want to use Sonar to further your sales.
At the moment, we offer Partially Addressed Advertising Mail. Partially addressed advertising mail is far better than name and address as data for name and address isn’t as extensive. Therefore, if you advertise using name and address, you are immediately minimising your prospects and missing an opportunity.
In contrast, partially-addressed mail allows a further penetration of postcodes. It moves your reach from being restricted – as indicated by figure 1 – to an extensive reach across a postcode – as in figure 2.
Nevertheless, we want to take our services to the next level. With Partially, you cannot mail to specific households within a postcode; you are required to mail to the entire postcode.
Our new service, Address-Only, uses Sonar to identify ideal clients/customers/donors for your business or charity. We then target those specific households within a postcode. That is, rather than targeting by postcode (as Partially Addressed Mail does), we will target using profiling. As a result, we offer you better reach, better accuracy and better target-marketing to the affluent.
If you’re interested in this service or in partially addressed mail to increase your target-marketing click here or email us at email@example.com.
If you want more information about Finely Fettled’s services, click here.
If you’re still unsure on Sonar there are plenty of resources to cover what I have discussed. You can see Graham’s blog here, which goes into more detail and accuracy. Or, take a look at our YouTube video where Graham talks through Sonar with the creator, David Griffiths.