This is the second in a two-part series on strategically reducing direct mail. If you missed the first article, you can go back and find it here.
Now that you know you can strategically reduce your direct mail spend, the next logical question is how to optimize your direct mail savings and funnel it into other channels.
How Much Direct Mail Is Enough Direct Mail?
As we previously discussed, the number of direct mail touches per quarter that drives a lift in sales will vary depending on customer segment. High-value, mid-value, low-value and new customers will all have a unique frequency. Once you’ve identified the optimal number of touches per group, you can dig a little deeper to determine the most effective way to reallocate those resources based on your own customers’ behaviors.
To illustrate, let’s recap and once again look at how one retailer determined the most cost-effective number of direct mail touches for their customers.
Incremental Sales per Marketing $ Spent by Predicted Customer Lifetime Value
As you can see from the table, this retailer’s medium and high-value customers and inactive customers need the fewest touches, and low-value customers maximize the investment with five touches.
You can use your own data to determine the proper frequency for your customers.
Where To Funnel Your Savings?
Once you determine the optimal number of direct mail touches for your unique customer base, it’s time to optimize your customers’ propensity to respond by channel.
You can do this by creating a direct mail response score and an email response score for each customer. Then, test varying levels of intensity to realize the impact of your most expensive channel, direct mail. Statistical modeling is the most effective means of determining these test-channel scores, but it is also possible to develop simple scoring based on past customer responses and interactions.
Let’s take a look at this in action. Using the same test as we leveraged in Article 1, we created the table below, showing the highest incremental sales per marketing dollar spent by channel preference bucket for high-value customers.
Incremental Sales per Marketing $ Spent by CLV Predicted Value
The customers in this test group who scored low for the email model resulted in negative incremental sales per marketing dollar spent, no matter how many direct mail touches they received.
Why? Because people who are not engaged online tend to be disengaged with the brand overall and don’t spend enough to offset the costs associated with additional touches.
However, in this example, customers who scored high in both email and direct mail are highly engaged, and therefore drove the best incremental sales per marketing dollar spent with five touches, while those with high email scores but low direct mail scores maxed out their spend at three touches.
You can use your own data to determine which customer segments are likely to respond to each channel based on the frequency of touches. From there, you know how to reallocate your own budget dollars to get the maximum incremental sales per marketing dollar you spend.
What Does Optimization Look Like In Practice?
Study the table below and you can see once again that in our test sample, the incremental sales per marketing dollarspent was the highest at three direct mail touches per quarter for our test group and the total marketing spend for 3 touches was $532,000 compared to $921,000 for five touches. Therefore, if every customer in this segment received just three direct mail touches per quarter, the retailer would see a cost savings of $389,000 per quarter.
From there, the retailer can take that $389,000 per quarter and reallocate some of it or all of it into higher-producing channels. They can connect with customers who are engaged with the brand on email and who will be motivated to spend more thanks to an increased digital communication frequency. And, the retailer can do all of that without sacrificing sales or increasing the marketing budget.
Making Sense of YOUR Data
Are you ready to optimize your spend and stop throwing money away on touches that don’t benefit you or your customers? You’ve already got the data you need to make these same determinations for your customer base. You just need a partner to help you leverage that data and determine your customers’ ideal frequency through precise modeling so you, too can determine the best way to optimize your budget dollars.