An Overly-Analytical Approach to Optimizing your Ecommerce Store

So you sell things online… awesome! That must mean you have a product / service that a lot of people really want. You’ve taken the time to develop / manufacture your idea, hire employees to scale it, and most importantly, you are ready to take the next step and grow.

Have you ever asked yourself, “Am I doing this right?” though? We all do! If you haven’t, you better start and this blog post will point you in the right direction on how to optimize your online strategy.

To start, there are four over-arching components that make up your store-strategy: (1) Customer Profiles (2) Order Characteristics (3) Customer Channel Preference and (4) Timing optimization. When these four variables align, your store gets a sale. Think about it – the right person who found the right product through the right ad at the right time buys! The more products you sell and the larger the diversity of your customer base, the more you will have to find different combinations of the above four variables to grow your company.

For the time being, we are going to frame out the above idea as follows:

1. Customer Profile = Cp
2. Order Characteristics = Oc
3. Customer Channel Preferences = Pc
4. Timing Optimization = To
S = Customer Who Purchased And Bought Based on 1-4

Cp x Oc x Pc x To = S

The more “S”’s you can find, the more your store will grow! So how do you find them?

 

  1. Customer Profile

    The customer profile is the variable you should be the most familiar with, since your customers are the people that you set out to sell to in the first place. However, as your business grows you will surprise yourself that there is hidden demand for your current and future products, too. To oversimplify the Cp variable, think about demographics, behavior and demand. Do you sell flowery dresses to elderly women who go to country club parties? Or are you targeting the middle-aged avid audio-book enthusiast who drives trucks for a living? This knowledge is typically your secret sauce and edge over the competition. Analytically, these are your judgment calls.

  2. Order Characteristics

    Order Characteristics are way more concrete as this data is in your store history. Think about using your products in the most profitable ways possible. The first question to ask yourself is “What product of mine gets my customer base to buy the most in the long term?” For example, an electronics company is going to want to sell you a cell phone first before you buy the cell phone charger for instance. As the cell phone triggers more purchases in the long term. Second, you need to understand what the most profitable products are to bundle together. When a customer buys the skinny jeans in your store, what do they typically bundle with those jeans to make a great looking outfit? Knowing how early to promote certain products over others and when and how to upsell your customer base with the right products makes all the difference between a store with linear growth and a store with exponential growth.

  3. Customer Channel Preferences

    Think about this variable in this question: “Where do my most profitable customers spend their time in the digital world?” The most important keyword: most profitable. Do not settle for any customer. Push yourself to find the most valuable ones to increase Average Order Value and boost growth. The easiest way to do this is to rank your online advertising channels by Lifetime Value (LTV). If a channel has a higher than average LTV and small amount of customers coming from that channel, go ahead and take some funds away from a lower LTV channel and buy some more profitable customers in that more profitable area of your advertising!

  4. Timing Optimization

    The last variable is timing. You can have the competitive advantage, have the most loyal customer base ever, and the greatest product strategy but if the message never reaches your customer than all is lost. To optimize this fourth variable, you need to find your business’s Lapse Point. A Lapse Point is the amount of time you have with a customer since their last purchase, to get that customer to buy again before you lose that customer forever. For example, someone selling skis is going to have a much longer Lapse Point than someone selling snacks. Understanding the window of time you have with your repeat customer base will help you master balancing your customer retention strategy with your new customer acquisition strategy (ie advertising).

    You might be wondering where to start – I suggest integrating your data into Glew.io and letting this software do the heavy lifting analytically so you can make the right business decisions!

  • Laura C. Brooks

    Great post!

  • Mark – yes! Thanks for putting this together. It really helps show the potential in a mathematical approach.