When average businessman hears about Cohort analytics, Latency Matrix or RFM reports, the only thing that arises in mind is pain or mess. You never know which side you should start from or what are the best practices for completing the analysis. Though there’s nothing too complicated – it is made to divide your customers by groups to work better with them via e-mail, phone or any other method of contact you may use.
A cohort is a group of people who make the same thing and whom we expect the typical ways behaviour in the future
Simple example of cohort sales analytics usage
Let’s say you sell toothbrushes. As per recommendations, people should change it at least once a month. Any toothbrush will be fine, so there’s no difference which one is bought, just the fact that it is ordered is considered as desirable shopper’s behaviour.
If the customer hasn’t ordered a toothbrush from you for over 2 months since the first purchase was made, you need to do everything to remind him/her about your store. Tell the shopper that the last toothbrush was ordered from your store and if he/she liked it, a new order should be placed once again.
In case buyer hasn’t ordered a toothbrush for 6-10 month period, you’ve lost him/her, as most likely his/her behaviour was changed and moved to another store. Customers with orders made over 12 months ago are considered as lost and you need to bring them back as new ones.
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The predictable action depends on product lifetime. Find out what is your customer’s normal behaviour.
How the cohort analytics can help you get those purchasers back? You can filter your customers by time period when they have placed their orders, for example, get the list of clients who have placed an order within last month. Then send them reminder that it is advisable to change toothbrush every month, forward details from dentists why it is important and try to make a second sale. It is our first simple cohort of customers, who have placed the order within one month and we want them to make a second purchase. The e-mail shouldn’t contain any discount code or coupon, but it need to be informative. Talk to your clients and they will keep the task of ordering toothbrush in mind and your store will be the first in the list where it can be ordered.
Next step is to find customers who have placed their orders within 1-2 month period. It is our second cohort. You should send these shoppers a kind of call-to-action e-mail in order to remind about importance of the toothbrush renewal and all horrors of using an old one.
Clients who have placed an order 2 – 6 months ago most likely are placing orders at some other store with toothbrushes or just do not care too much about their dental health. You can try to convince them with some offer or code in order to bring them back to your shop and turn these occasional buyers into your loyal clients.
While customers who haven’t placed an order for over 6 months should be treated differently, you should take care about them as well.
Filter customers by last interaction, to help them move forward
That’s simplest Cohort report with Recency as main parameter. This analytics can be executed right in Excel.
Just export the list of orders from your store for the last year, open it in Excel and in the new sheet insert “show unique” or “unique” to get the list of unique e-mails and in the next column add “sumif” formula to show the latest order date made by each customers.
Filter the list using dates to get your desired cohorts. You’ll get the lists of buyers to work with or send an e-mail via any mail client. According to the RFM model, a customer who has recently interacted with your store is more inclined to accept another interaction that you initiate.
Almost all ecommerce sites have 60% of one-time buyers
Though when working with cohorts this way you might miss some important points, like one-time buyer or customer who has placed 10 orders this far. You will treat the same way two customers who have spent $10 and $1000 as only the last order and the fact that it was placed will be taken into consideration. This way all the people, who have left order at you webshop are treated basing on their last purchasing action.
More complete analytics is shown in Recency, Frequency, Monetary report. It considers the number of purchases as well as total sum that customer has spent at your online store.
These types of reports you can check for your Magento store with Store Manager. Learn more about it or download it right away here.
This post is provided by guest contributor Oksana Semenyuk, CMO at eMagicOne – company offering smart and convenient ecommerce solutions that make maintaining online business very easy and effortless.