Only those who analyse data with a purpose and gain the right insights from the results can optimally harness this treasure trove of information. This overview showcases which information is essential for data processing when it comes to e-commerce.
Which data is important for e-commerce?
Data is raw material which only shows its real added value once it has been processed. A problem with this: nearly all processes in e-commerce result in huge amounts of digital information from which interesting insights can be gained with the use of suitable software. This can lead to an immensely large competitive advantage. But which data is truly important?
The answer to this question depends on the respective industry and the individual company – after all, each branch and each organisation has its own rules, KPIs and goals for which the data processing could be useful. This makes it nearly impossible to make a concrete statement. But a statement can be made about which data has a generally high relevance for e-commerce.
Impressions
Impressions are the frequency at which ads or content are presented to interested persons. This can be via paid ads on websites of third parties, via search results lists, social media platforms and similar sites. Impressions are one of the best controllable measurement mechanisms that companies can have, as they are nearly solely based on the budget that the company allocates to its various activities.
Reach
Reach is the entire number of all those individuals who saw the content. This can be opt-in email subscribers, Facebook followers, and subscribers to loyalty programmes. Reach can be best boosted through consistent campaigns – social media, email or in another way – with the aim to address subscribers, followers and other interested persons. The better a brand and its message are defined, the more effective campaigns will be to improve reach.
Engagement
Engagement describes how many followers and subscribers (reach) interact with the content. This can be acquisition-based activities such as click-throughs, as well as non-acquisition-based activities such as likes and shares. Engagement profits especially from frequent activities for promoting a brand and a product.
Cost per action (CPA)
This figure shows how much money had been invested until a purchase or booking was made, or a request sent, for instance. When these costs are higher than the overall turnover generated, this is not good. The CPA can be lowered by creating a campaign that is better tailored to the target group.
Social media figures
These figures can offer great added value for e-commerce companies, as they are the most important KPIs for social media engagement which should be frequently included in data processing: likes per post, shares per post, comments per post, clicks per post.
Shopping cart abandonment rate
This rate shows how many people put something in their shopping cart, but who left the website without actually making a purchase. This information is important for determining if the website or shopping cart contains barriers which make the payment process more difficult.
Average order value (AOV)
The AOV is the average price the customer pays for the items in their shopping cart. It is an important KPI, as it measures the effectiveness of the marketing. The AOV can be increased with the sale of extras, the use of loyalty programmes or other, more basic elements such as price policy and product quality.
Conversion rate
The conversion rate is the entire number of orders/sales divided by the entire number of visits to an online shop. Understanding this rate is decisive for identifying how much traffic is needed to generate the desired number of targeted sales. The conversion rate can be determined, for instance, per channel (AdWords, SEO, Facebook), product category and campaign.
Customer retention rate
The retention rate can be best defined as the percentage of customers who the company retains as regulars over a certain period of time. The higher this value, the better. When calculating it, it is important to not include new customers in this group.
Customer lifetime value (CLV)
The CLV is the overall turnover that an e-commerce company achieves over the course of time with a single customer. It is a very good KPI for estimating the average customer satisfaction, their loyalty and the value of a brand. A high CLV hints to the marketability of a product, to brand loyalty and frequent sales by repeat customers.
Churn rate
The churn rate measures the number of customers who have left the company over a certain period of time. Depending on the industry and sales approach, a lot of time may be invested in the individual user experiences. It is always easier to sell to existing customers than to win over new ones.
How often should data be processed?
Each of the data sources mentioned above can provide interesting information. Which is why it makes sense to frequently document and review it. However, this does not need to occur every day.
Some KPIs should be reviewed weekly to ensure the company is well positioned. For instance, these could be website traffic, social media engagement, and impressions.
Irrespective of your weekly measurements, bi-weekly measurement values are best for larger spot checks and are less influenced by fluctuations which can appear within a certain week. These bi-weekly KPIs can be the AOV, CPA and shopping cart abandonment rate.
The monthly data processing of KPIs is recommended when it comes to multi-channel engagement, reach and bounces when adding items to the shopping car, as well as other micro-conversions.
Quarterly KPIs are the most strategic. They describe the long-tail activities and show if a company is flourishing and growing over the long term. The main values are, for instance, the email click through, CLV and subscription rate.
