Are you just measuring your online store’s sales in a silly way? I’ve really noticed that several online retailers look at figures in an unusual way. Because of its structure, an online store is different to a physical one. Online store sales should be measured with the help of various models.
Physical store figures do not work online
Several online retailers have a background in physical retail. The metrics have come from the supermarket world. I repeatedly run into a situation where sales are only measured in terms of one day’s sales or by comparing them to the previous day.
I usually stop the retailer right there and start to shake things up by saying: “Start with the basics!” A small or new retailer, in particular, generally tries to achieve sales happen by force. If the whole start of the week was quiet, the store’s sales will not develop by themselves by just believing hard enough that sales will grow.
Sales usually correlate with actions. Actions can be the removal of barriers to buying or re-examining pricing. First, you need to understand the cause and effect of online retail. If make changes to my store today, it may have an effect on store sales next week or next month. If products are easier to find you cannot compare old and present store results.
Something else that badly distorts sales figures is campaigns. For example, if you sell everything in the store at a discount of 25%, this will probably affect your store’s sales. When you compare weeks after discount sales, remember to take the effects of campaigns into account. Big discount campaigns often affect sales after a campaign, for example.
From mere daily sales to the bigger picture
The first step towards understanding the entire entity is following the bigger picture. Advanced online retailers use various rolling models per the examples of Amazon. For example, they track rolling sales over 7, 14 or 21 days. That way you can compare how sales have developed over one rolling period and compare them to earlier results. This gives a good overall picture of store sales development for several online stores.
If rolling sales models are all Greek to you, you should compare weekly or monthly sales instead of days. This perspective will even out individual days’ sales spikes and give a better overall picture of the direction of your store.
In the big picture, it is not worth making far-reaching decisions based on one day’s sales. This is especially true if your store is small or medium-sized. Larger online stores, on the other hand, can take steps in minutes. However, they are playing a completely different game and operating with different resources.
Note that sales have sectoral difference. Some online stores’ sales are evening-focused, while others sell more at weekends. The weather and public holidays can affect the development of sales. What is crucial is to know your own business and to understand why sales develop at certain times.
The lesson is to try to level out sales spikes, because spikes are always difficult to predict. Predictability, in turn, makes it easier to plan future steps.
From conversion to cohesion
Another issue which causes misunderstanding is conversions. Online retailers often talk to each other about developing online store conversion and conversion optimisation.
As a term “conversion” is a little misleading. A mathematician friend told me that online retailers have taken a fine term and started using it wrongly. In the online retail world, conversion means actions in the store that are advantageous for the merchant. So, in practice, this means visitors’ purchases: the more visitors who buy, the better the store’s overall conversion is.
Measuring conversion alone, however, makes the world look very black and white. New merchants, in particular, are needlessly shocked by changes in conversion figures. At the initial stage, the store usually searches for a niche, both in terms of external look and selection. In addition to this, optimizing customer acquisition often takes several months. All these actions affect conversions.
What happens?
Instead of conversion alone, it’s worth focusing on what really happens in the store. How do new customers move around the store? Do they find their products easily? Is comparing products easy? Does the store engender trust? Is payment easy? How can I get the customer to buy again?
It’s worth monitoring these using Shopify’s own analytics, Google Analytics, and by using recording apps such as Lucky Orange and Hotjar.