Relation between Purchase Frequency and Retention in eCommerce

Evaldas Mdata, retention, segmentation0 Comments

Stores have been smartening up their places and window displays to match the new found purchasing power of their customers from the very first days of their existence. Some would go even further with this like “Barbershop”, the custom in the 16th and 17th centuries of spending time in a barbershop by harmonizing to a lute or guitar provided to entertain customers waiting in line. A small amount of something added to an actual purchase in a market always encourages the customer to return.

And although online businesses have so many advantages over brick and mortar retail stores, they wanna look pretty much the same as their counterparts, and are always thinking up new ways to promote products, retain their customers and turn them into repeat buyers that would keep coming back for more.

A naturally free and easy manner to keep these loyal customers happy is by measuring your store’s average purchase frequency and using these figures to create an attention-grabbing advertising, marketing campaigns and outreach strategies. Integrating these key business metrics you can transform the performance of your business without dissipating money, time, or effort.

Okay, that sounds good, but what’s the catch? There is no catch. It’s all fair and square. These new powers will take us far ahead, so let me continue by asking a question:

Relation between Purchase Frequency and Retention

What is a Purchase Frequency and Does it Really Matter?

Basically, your purchase frequency is the average number of purchase decisions that a customer makes at your store within a certain period of time, and a good sign of the sustainability of a business.

The exact nature and extent of this metric is as clear as it could be: making customers habitually come back and use your product or service with a frequency greater than chance, and of course, increase your sales. An elevated purchase frequency is responsible both for raising revenue and increasing customer lifetime value

To calculate your purchase frequency, divide your store’s total number of processed purchase orders by your number of unique customers. Once you do that, you can start collecting data, which can be used to infer the dependence of two variables: whether your shoppers are able to finish their purchases at a certain time and when the most profitable purchasing activities take place.

Purchase frequency and repeat purchase rate help you understand and stick to what your customers really want. This data gives you an invaluable insight into what value your most profitable customers are looking for their money.

Now, let’s dig a little deeper into how we can measure the value of purchase frequency and the effects and  likelihood of hot leads (return customers).

the value of purchase frequencyCalculating Purchase Frequency (PF) with Repeat Purchase Probability (RPP)

We’re going to illustrate some of the necessary PF calculations of sales from an online retailer.

necessary PF calculations of sales

This sample dataset refers to the number of customers orders that plummets by a large amount after the first purchase. Sorted by this sales report we will quantify the proportion of the total sales by a customer for a certain time period. We take an average order value (AOV) of $40 and multiply it by the projected revenue.

the proportion of the total sales by a customer for a certain time period

It is perhaps no surprise to see that the biggest revenue is brought in by first-timers, yet the figures tell a different story when we compare it to the repeat buying frequency. What it all amount to after all is 41% of a company’s sales turnover.

The interesting part is how to calculate the chances of the average first-time buyer who spends many hours juggling figures making another purchase. That is the way it is: your store’s repeat purchase rate calculation is derived from repeat customers (x+1) divided by all purchase occasions on the site (x) for a given date range.

the chances of the average first-time buyer

As you can see, chances of shoppers returning again almost double once a customer makes a subsequent order, and keep doing that through successive rounds increasing the total revenue per customer. Moreover, we can measure the value of trying to enhance the likelihood of loyal customers ordering from you again by using the same numbers above!

The majority of customers who purchase for a first time are in the process of filling a need, which makes conversion rates in ecommerce extremely volatile. But, let’s say we could figure out a way to prompt repeat purchases, consistently lifting the conversion rate for second purchase, by 10%.

Even a small increase in your secondpurchase conversion rate would matter. So the final RPP from first to second purchase would end up being lifted to around 22% instead of 20%, as shown in the chart above. Now, we can calculate the increased number of customers that would become repeated buyers. The more customers who come back and buy two, three, or even ten times, the more important each and every one of them is in a long-term relationship.

If we had 75,000 customers who made one purchase, we could measure the quantity of ascending orders with our 20% RPP and perform the following calculation:

measure the quantity of ascending orders

From there, we can initiate conditional probability distributions of the repeated buyers multiplying these probabilities by the average value of each customer transaction, meaning some customers will only buy a second time while others buy on a regular basis.

onditional probability distributions of the repeated buyers

Using this information we can sum up the total revenue, which is approximately $122,000. This number gives us the value of the lift coefficient that we determined experimentally before. With these proportions, companies can get an even more detailed estimates of the value in their customer list, and determine the additional revenue per customer:

This framework helps you estimate your maximum affordability when trying to entice existing customers to buy from you again. The relative risks for the third purchase are higher than those for the second, but it delivers a much higher value. If we calculate a similar lift, the value of each second time customer purchase rate steadily increases to $170 due to the contribution of familiarity with the offer.

Calculate the value of retention marketing

Retention marketing calculator

 

So now when you’re looking for an opportunity to engage different market segments, and even customers at an individual level, you’ll have all the relevant data to get as many conversions as possible at the target costperacquisition (CPA) you set with its help.

Keep on making these calculations and estimates for assessing the variability of your own stats before taking these templates as a law. Keeping up with frequent changes in customer buying behavior pattern ensures that the consistency of customer acquisition and retention orientation stays aligned with your customer purchasing preferences.

How Can You Increase Your Purchase Frequency?

As a small business you need to build an ongoing relationship with your customers and show that you care, thus raising brand awareness with your target audience, and the time that you spend researching your customers and users, will pay off handsomely.

build an ongoing relationship with customersEmail Marketing

Email marketing offers an especially effective way to bring customers back to your site, engaging, and purchasing. The the key is personalization: delivering a consistent, highly-relevant and engaging content and promotional offers at the right time to create new opportunities.

If a customer has ordered from you before, a personalized offer for 10% off will encourage them to come back and purchase from you again, giving you an advantage over competitors.

The cold leads (potential customers) require a lot of attention, because they are unaccustomed to the whole process. That’s why it’s often believed that second-or third-time buyers don’t need as much since they’ve been through every stage of its passage. But they face their own unique challenges that should not be ignored. Reward programs, coupons and freebies can also elevate your purchase frequency building deeper bonds with these customers.

Remarketing

Remarketing (aka retargeting), is an immensely powerful tool that helps you improve purchase frequency and brand awareness when integrated into an ad strategy. It targets customers based on the websites they viewed or visited by showing relevant ads across their different devices reconnecting them with the previous or similar products.

Once they’re reminded of one or more of the products or services of the preferred brand in the mind, they’ll show enthusiasm and come back and make another purchase, no matter the amount of purchases they did in the past, so invest more in customer loyalty.

invest more in customer loyaltyHow Does Knowing Your Purchase Frequency Impact Your Retention Rates?

Knowing your purchase frequency enables you to truly leverage that valuable data and structure personalized marketing efforts around your customers’ behavior profiles bringing them into the cross-touchpoint digital experience. And the freshness of this data is exceptionally important for accurate targeting, personalization and retention.

Notice that over half of online shoppers are more likely to tread the floors of a site again if it delivers retention and personalization at scale. Over half of customers indicated that they would be willing to share personal information to the legitimate reputable companies, as long as it is treated with respect, and they see some benefits. After all, how can you personalize your marketing plan and customize your sales pitch without reflecting on your customer identity data.

You don’t have to be a genius to see that the more you make the world go ’round with these marketing initiatives, and keep customers coming back, the more likely they are to continue buying from you. But, if you poke your head through this opening: profitability of acquired customers, you can see that most customers are only 27% likely to shop with you again after one purchase. However, the purchasing activities nearly double the profitable menu to 45% once they make a second purchase and spike conversion to more than 50% after the third.

The situation prevailing in marketing and advertising is that retention is boring and optimization (especially hustling up new customers) is sexy. That is the problem, and too many companies are evading the issue. My guess is that they have overreacted to a few throwaway lines by Alec Baldwin’s classic “Always Be Closing” speech in the film Glengarry Glen Ross. I don’t believe that the sales representative makes the contact with customers, introduces the company’s product, and closes the sale. If you think you can do this, you have just missed the boat because it doesn’t work that way. What you should be doing is “opening” a relationship. The sales transaction is just the start of the relationship, not the finish. Loyalty is a repurchase behaviour, loyalty is a repeat purchase frequency, loyalty is even the probability of the purchase. So make no mistake, I mean one of the limiting beliefs that prevents business owners from talking about getting new customers, is to approximate the market with something like -“Our usual discounts for large orders apply to you as a regular customer, and we are exceptionally doubling these to 10%”, or “A really good bounce back catalogue can also whet our customers’ appetites for merchandise” otherwise they are doing half their jobs. Simply banish the overly-inspiring idea of “closing”.

Creating personalized experiences by utilizing technology and business data for analytics and action can make dream become a reality. We live in a world of overchoice. We have so many choices that one of the most difficult things we have to do is to make good decisions. And natural approach tends to be most effective with customers who prefer a persistent but low-key way of building trust slowly.

If you would like to get a sample excel sheet for evaluating your own PF relation to RPP just drop me an email to e.miliauskas@stacktome.com

 

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