In today’s digital world, the volume of data generated by retailers is enormous and what to do with it can be overwhelming. We’ve worked with pure-play and multichannel retailers for many years and learnt the biggest bang-for-buck quick wins for getting the most out of your data. Here’s our top six priorities.
1. Automate your trading analytics
You need a trusted view of business performance, with built-in ability to deep-dive to any level. Release valuable resource from spreadsheet-production; get your period-to-date, budget and year-on-year comparisons automated for traffic, conversion, demand, sales and returns, margin, stock cover. Get red flags out of the box.
Datitude has a simple-to-use report builder that allows you to create all these reports in literally a few seconds. Starting from trusted data sources, anyone in your organisation can design and build reports, to share as PDF documents or extract underlying data into Excel for further analysis. Reports can be configured to send automatically on a regular basis, so releasing valuable time for you and your teams, each and every week.
2. Segment your customers into similar groups
Segmentation is a well-established technique used by marketers to group together customers who behave in similar ways. Once you’ve created your groups, you can understand how they’ve behaved in the past and use this insight to drive future behaviour.
RFM analysis (recency, frequency, monetary value) is one such technique. It’s a proven marketing model used to identify which of your customers are most likely to purchase again. It brings together how recently, how often and how much money a customer spends with you. The model predicts that the most recent, highest frequency and highest monetary value customers will be the ones that are most likely to buy again.
3. Understand your customers’ lifetime value
A customer’s lifetime value is a measure of their worth to you over time. It is the total of their sales orders less any returns. Knowing this allows you to confidently set limits for customer acquisition costs.
A good customer data platform will allow you to compare the lifetime value of different groups of customers. Here are some examples:
- Lifetime value by acquisition channel and by RFM segment are incredibly useful, giving you data to optimise marketing actions.
- One recurring theme we see is that customers who purchase a mix of mark-down and full price product have consistently higher lifetime values than those who always shop full price.
- For retailers selling products with high returns rates, with women’s fashion being a prime example, being able to differentiate between truly profitable customers and those pesky, persistent returners is gold.
- And the ability to see where your most profitable customers are geographically can help in many ways: planning stores, collection points, localising social spend. Here’s an example of how Datitude can help you visualise your data:
4. Understand which of your products drive customer loyalty
All retailers know which products are their best sellers, but more valuable is understanding which products create the most loyal customers. Do you know if your best-selling products are creating loyal customers? Or do those product purchases result in customers who buy once and never return? At Datitude, our Loyalty Index tells you which products are the ones that your customers like so much that they keep coming back.
The Datitude Loyalty Index differentiates between products that are underwhelming and those that exceed expectations. It’s important because it means the difference between a one-time buyer and a repeat customer. We do this by looking at the number of repeat orders generated from each product bought in a customer’s first order. From here, we calculate the loyalty index.
5. Pinpoint when customers are most likely to place their next order
Do you know how many days elapse between your typical customer’s first order and their second? Many retailers mistakenly assume that the average (the mean) number of days between one order and the next is a useful metric; in truth, the mode and the median number of days are much more helpful.
Why is this? Most customers, if they are going to place a second order, place that 2nd order very shortly after placing their 1st. In fact, it becomes increasingly less likely as time goes on that they will place their 2nd order.
Firstly, a bit of maths! When people talk about an average, they are typically talking about the “mean” – it’s when you add all the numbers together and divide by how many numbers there are. However, there are a few different ways to calculate an average. Here, as well as talking about the “mean”, we’re also talking about the “mode” – the mode is the value that occurs most often – and the “median” – the middle number when all the numbers are listed out in number order.
Here’s some real data from two different online retailers to show the mean, median and mode averages for the time between 1st and 2nd orders. We’ve taken the number of customers each retailer acquired in a year and then found how many of those customers placed their second order within 365 days of their first. We’ve calculated the mean, median and mode averages and shown the results here:
|Measurement||Retailer 1||Retailer 2|
|Customers acquired in the year||99.5k||165.2k|
|Of these customers, the number who’ve placed a 2nd order within 365 days||30.5k / 30.6%||44.7k / 37%|
|Mean days to place a 2nd order||93 days||105 days|
|Median days to place a 2nd order||70 days||83 days|
|Mode / Most Common Day||Day 0||Day 0|
|% of customers placing a 2nd order within 1 week of their 1st||15%||21%|
|% of customers placing a 2nd order within the 52nd week after their 1st||1.4%||1.8%|
What does this tell you and how can you use this data?
The most likely day that a customer places their 2nd order is consistently the same day as their 1st! As you’ll see in the graphic below, which shows the number of customers placing their 2nd order by the number of days since they placed their 1st, the likelihood that a customer places their 2nd order on any given day decreases as time goes on. For our two retailers here, customers are more than ten times more likely to place another order in their 1st week than almost any other week. And if a customer hasn’t placed a 2nd order, the likelihood that they will do so declines with each passing week.
The median shows us that half of customers placing their second order do so after 70 and 83 days respectively. This means that after around 10 to 12 weeks, half of your customers who are going to place a 2nd order of their first will have done so.
So, how do you use this insight? Actively marketing in the time immediately after an order, when customers are predisposed to repeat purchase, will reap dividends. Communications that work quickly after customers are acquired to build loyalty are incredibly valuable. Emails that offer free delivery or promotions if a repeat order is placed within a defined time period work really well.
6. Get a single view of your customer
Shoppers who buy instore and online have a 30% greater lifetime value than those who use a single channel (1). It’s vitally important to get a single, unified view of your customers.
The Datitude Platform de-duplicates customer data to identify individual customers, making it easy to truly understand your customers’ behaviour. Here’s just a few reasons why this is important:
- It gives you certainty about who your best customers are by making sure each customer’s lifetime value is correct.
- You can identify how multichannel customers interact with your different sales and marketing channels, so you can target them using the right channel at the right time.
- You can optimise your marketing spend by never sending a duplicate communication to a customer or prospect.
Datitude has designed a number of very sophisticated processes to de-deduplicate customer data. For e-commerce data, we typically use email address to de-dupe. This also works for retailers with guest check-out processes, where email address can be used to identify individual customers.
Direct mail campaigns require a different approach and Datitude is set up to use a number of de-dupe keys, including variations of postal addresses, allowing you to decide whether to mail at an individual, household or residence level.