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(Last Updated On: May 4, 2021)

Sharpen Segmentation to Maximize Responses to Campaigns

Hey there! Welcome to Acquigo blog.

The first and foremost step in campaign management is defining the goal along with the segment that you want to target.

We hope that you have moved from demographic to behavioural segmentation. If you haven’t, its time you did.

But do we get our segmentation right

Ok! We know that there is no direct metric to evaluate this and we need to find one.

Tracking response rates could be a great place to start. If the segments are right, the campaigns will be relevant and responses, great.

At the very least, if you do not get around 20 to 30% responses on your campaigns aimed at existing customers, it may be time to define and sharpen your customer segments.

In this article, we will talk about

  • The need for sharper segments for your campaigns
  • How sharper segments positively impact campaign response rates and
  • What you need to do create sharp segments

Let’s jump right in.

The art of segmenting customers

Segmentation flatters to deceive. Because it involves numbers and data, most marketers see segmentation as a left brain activity and take a functional view.

However, we think segmentation is a ‘whole-brain’ activity where creativity is as important as analytics.

Unless you put yourselves in the shoes of your customers, visualize their behaviors, needs and wants and see how well you can use your data about them to arrive at segments, your segments would be far from ideal.

One of our banking clients had tons of rich customer data and a campaign management platform, but hardly used either of these assets.

When we started working with them, they had a business goal which was to drive revenues from credit card usage.

To achieve this, the client had tied up with three big retail brands, so they could send exclusive offers to their credit card customers.

And they wanted us to help target customers with low credit card usage, to get them to start using their card again.

The client had a credit card customer base of 2.3 Million and they defined inactive / dormant credit card holders as those who have not used their credit cards in the last 45 days.

This is how the campaign brief translated into.

01

The client was hopeful that by running this campaign they would be able to

reach a large audience base and even at about 2% conversion, they would be able to get about 4000 customers to start using their credit cards again. And that would be a good for a start.

However, we thought that the audience was too global to reach, and anticipating just a 2% response actually killed the whole purpose of segmenting audiences for campaigns.

We recommended that the client add a few more parameters when segmenting customers for the targeting to be more relevant.

But the client was under immense pressure to quickly launch the campaigns and start driving revenue, and so rather reluctantly agreed to include just “one” additional parameter to segment customers.

Having a strong understanding of customer behavior, we knew that different customers had different spending patterns when it came to credit cards. And we wanted to include that as an additional parameter when segmenting the audience.

Once we included card usage frequency to the segmentation criteria, the brief looked like this.

02

Note: Since the first set of customers still fell in the active batch as their regular usage frequency was less than the target criteria, we recommended just a relationship management campaign to nudge them.

The second set of customers were categorized as lost because they stopped using the card for more than 45 days, compared to their normal usage frequency of once in 15 days. And we recommended win back campaigns for them.

When we showed how just the addition of one parameter turned the tables, our client was thrilled.

Our client began to see that the campaign would have flopped if all of the 197,000 customers were treated as one segment.

Now with a complete turnaround, thanks to a sharper segmentation, the client was more interested and unsurprisingly wanted to see if we could use one more parameter to further fine-tune the segment, which we were happy to do.

And so, we brought in the average number of credit card swipes into the segmentation, as we knew the bank would get an interchange fee with every swipe and that this will directly impact the overall business goal.

Once we applied the ‘average number of credit card swipes’ variable to the segmentation criteria, the lost category of customers broke further into something like this -

03

Note: Although both categories of customers were ‘lost’, we laid a greater emphasis on the latter by sole virtue of the number of times they swiped their credit card and the potential revenue for our client.

We recommended that our client assign offers of the highest value to this segment and that there must be a personal connect to reactivate them.

Our client fully agreed with our recommendations and gave us the approval to run all three campaigns as opposed to the single one planned earlier.

We went ahead and developed the communication, addressing the sensibilities of each segment and mapped the most relevant offers to the specific customer segments.

We ran a 4 wave campaign, targeting customers across email, SMS and call center, and the results were astonishing.

By defining segments sharply and smartly, a campaign which was supposed to happen like this

04

turned out like this.

05

Needless to say, the client was on cloud nine on seeing an average response rate of 31%.

After the grand success of the campaign, the client became a huge believer in a sharper segmentation for campaigns.

The Learning

In the above example, even if the client had gone ahead and run the campaign as they had originally planned, they might have still got about 4000 odd customers to start using their credit card.

But, because of the sharper segmentation, the client was able to activate approximately 52K customers, which is 13X higher.

And the best part is that they were able to achieve this with just a simple shift in the approach to segmentation with ZERO additional investment.

It all goes to show that the sharper the segments, the greater the relevance of your campaigns to your customers and the better their responses to your campaigns will be.

If you happen to be one of those marketers who aborts an outbound campaign just because you have an insignificant number of target customers, (which is the result of your segmentation criteria being stringent), it’s high time to stop doing it.

And here’s why.

The fundamental reason why every marketer is a fan of segmentation is that campaigns are relevant to a segmented audience. You are able to send them communication that is relevant to them.

In fact, I’m sure that we would all love to run “n=1 campaigns”, where each campaign is personalized to individual customers, if it is practically possible.

That being the case, why would anyone abandon campaigns because the number of eligible customers for them, is miniscule? Isn’t that why we ventured into marketing analytics techniques like segmentation?

7 steps to make your segments sharper

Now that we see how sharpening your segments improves customer responses to campaigns, it is time to dive right in. Here are 9 steps that can help you.

  1. The first step is to ensure you capture all customer transaction data in a single location. Depending on your budget, you can invest in a Customer Data Platform or DataMart or Data Warehouse.

  2. The next step is to make a comprehensive list of derived fields that could represent customer behavior over time. For instance, Average Monthly Balance, Average Quarterly Balance, Average No: of Transactions, Average Ticket Size etc.

  3. Now, build rules / queries to ensure these metrics are calculated and updated for each customer, preferably in real-time or at least by the end of day.

  4. Once you have this data, the business end of the segmentation begins. Start by visualizing customer behavior that could be leveraged to achieve the campaign goal. Don’t worry about data yet. Start with abstraction.

  5. List down the fields that can represent those behaviors. If you don’t have data fields, it’s ok to go ahead with available fields. Assign the value range for each identified field.

  6. Define core segmentation criteria using the most important fields from the identified list. Make a note of the number of eligible customers.

  7. Now, keep adding additional fields to the segmentation criteria and see how the target list keeps changing. Keep going until you come to the point where you are sure you have included all relevant criteria.

It’s highly unlikely that anyone would get their segmentation right in their first few attempts. You keep getting better at it as you go along. Keep altering segmentation criteria in subsequent campaigns until you get it right.

You could also use a control group to validate the efficacy of your segmentation criteria so you know what changes need to be in the next campaign cycle.

Summing up

Sharp segmentation is one of many obvious things that are overlooked by marketers. Sharpening your segments won’t just help you target your customers better for a specific campaign, it also uncovers different audience segments that you could target for other campaigns you might run in the future.

Sharply segmenting your audience is just the beginning of a long journey. There are a lot of other things that should come together to complement your sharper segments to make your campaigns successful on a consistent basis. We would be talking about those in subsequent articles. Keep watching this space.

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