In shop optimization, the conversion rate is usually the central KPI in focus. And it’s true that this key figure strongly influences the success of e-commerce.
However, people often forget that there is another value that has a similar influence on e-commerce revenue: the shopping cart value.
Of course, the shopping cart value is essentially dependent upon the range of products that are offered in the online shop. A provider of drugstore products will have smaller shopping carts, while an online furniture shop’s carts will have three- to four-digit numbers. But even if the average shopping cart value is small, it pays to focus on this key figure shop optimization. In this way, online marketing can also contribute to the optimization of your shopping cart.
A small profit and loss statement can show the shopping cart’s leverage. This shows the gross income of an online shop, which can be displayed as a profit margin of the second level, after the deduction of acquisition costs. See below:
Gross income = Visits x [Conversion Rate x (Shopping cart value – Acquisition costs) – CPC]
Using the example monthly value for a small shop, this is calculated as:
Gross income = 150,000 x [3% (60 € - 30 €) – 0.75 €] = 150,000 x (0.90 € - 0.75 €) = 22,500 €.
To now determine the influence of the shopping cart value on the gross income, this value is derived from the shopping cart value. We find:
In our example, this means that an increase of the shopping cart value by one Euro, with stable acquisition costs and CPC, leads to an increase in gross income of 4,500 €. This "lever" is unequally higher than additional visits, with which an increase of one visit would increase the gross income only by 0.15 €. As with the conversion rate, this means that before you work to increase shop visits, you should exploit the potential of higher shopping cart values.
As with all key figures that significantly impact your profit and loss statement, you must also look at what is in the size of the shopping cart’s value. Normally, shop operators have an average shopping cart value in their sights when they talk about optimizing their shop. Either they simply divide the sales of a period by the number of orders, or they derive an average shopping cart value from the shop system. There, the shopping cart value is usually calculated as with Google Analytics. But while the shopping cart value in an online shop must correspond with the actual revenue, the information in Analytics depends on how the e-commerce tracking in Analytics was established. What matters here is the amount of basic taxes and shipping costs.
Basically, you should make sure that you’re looking at the right amount when you look at the shopping cart value. When optimizing shopping cart value, the shopping cart value is linked to income value. The success of the company does not include value added tax and or returns. Because returns generally can only be recognized at a later time, you must establish an average return rate when determining and optimizing shopping cart value. Clothing shops generally have large shopping carts, because a comparatively higher portion of items ordered are returned. Discounts should only be considered if these play an on-going role. In contrast, shipping fees can be considered in net income, insofar as the company’s internal costs for shipping are considered in the acquisition costs.
After all the adjustments, the number of items ordered as well as their price is the relevant influencing factor for shopping cart value.
When optimizing the shopping cart, it should above all be considered how many conversions you can achieve and how many sales you require in order to achieve a determined gross income. The gross income is the amount, which, after the deduction of acquisition costs and the direct online marketing costs, remains to cover the overhead costs. The determination of a minimum shopping cart value can thus be done as follows:
Overhead costs = Visits x [Conversion Rate x (Shopping cart value – Acquisition costs) – CPC]
Following the shopping cart value, we arrive at the – somewhat complex – operating expression below:
If you consider that CPC/CR = CPO, that is, Cost per Order, our rule becomes even simpler:
Because V x CR (visits per conversion rate) is the conversions, the targeted shopping cart value has to cover, at the very least, the following:
In our example, the minimum value for the shopping cart with overhead costs of 20,000 € is thus:
The optimization of the shopping cart value should begin at the source, namely, in the shop. The price politics are really the primary instrument for increasing shopping cart value. Above all, you should exploit your price-setting freedom. In this, software that adjusts the price dynamically to the market situation can help. Whether and how the shopping cart value can be sustainably increased naturally depends, above all, on unique selling points and on the competitive situation.
After the sale price, another direct factor that is important is the number of items. A higher number of items can have a positive, but sometimes also a negative effect. For starters, a higher number of items can increase the sale and distribute the overhead costs of the order to a larger number of revenue drivers. But if the shipping costs are compounded, or are even null, a higher number of items can, at some point, have a negative effect on the order. This should be a problem in rare cases, however, and would indicate the basic defects in costing.
You have several possibilities for increasing the number of items bought by a customer. Cross-selling are such measures in which complementary products are offered. Under the heading "Often bought together", supplementary and complementary products are typically offered. "Collaborative filtering" works in a similar fashion, where further complementary products are offered under the heading "Customers who bought this product also bought". Finally, we have upselling, in which higher-quality and higher-priced alternatives are offered.
With all these efforts, you should however not lose sight of the customer’s motivation. Is he or she actually motivated to buy more than he or she originally planned? Are the products offered really attractive, or only very similar? It is important to point toward the advantages of a larger shopping cart in online shops. Corresponding call-to-action texts can address price advantages from ordering additional items; if necessary, refer back to savings on shipping costs or highlight the saving of time and comfort when several items are ordered at once.
An important pre-requisite for increasing the shopping cart through increased order size is, above all, trust in the shop operator. Therefore, put the emphasis on existing customer recommendations. The online shop should also differentiate between existing and new customers in cross-selling and collaborative filtering.
A final, important question is when to use cross-selling and upselling. It is fundamentally advisable to place these product recommendations only in the shopping cart or in the checkout on the online shop, in order not to distract the customer from the product or landing page. For such recommendation placement, you should certainly use A/B tests or look for best practice examples.
Even if the customer does make the final decision about what to put in his or her shopping cart, this decision is prepared by online marketing. This means steering the customers’ expectations and creating an online marketing budget based on the targeted shopping cart value.
We can assume that customers have clear expectations about the range of their shopping cart when they begin their product research. Someone who would like to buy a camera will focus on this product. Someone who wants to buy a new spring outfit or sports equipment will look through several items when beginning their product research. Finally, experienced online clothing shoppers will order several sizes of a piece of clothing to circumvent fitting problems.
This shopping cart model should be considered in the formulation of display texts and meta descriptions. Where product research normally concerns a single item, notices about complementary products can be sensible. "Large selection and professional accessories" can be a promise that can lead to a positive decision to click. In fashion, this could include accessories or sets that can give an indication that the shop has further attractive offerings for complementary products.
In addition to the emphasis on the content in shopping cart decisions, this naturally also has consequences for online marketing expenses. Where click prices are high but shopping carts are small, the efficiency of paid-for online advertising is limited. Therefore, you should also consider the shopping cart when calculating the paid-for advertising budget. The following short calculation shows this:
First, for the Adwords budget:
Budget = Visits x CPC.
Further sales can be obtained with performance marketing measures. For this, the following connection is valid:
Sales = Conversions x Shopping cart = Visits x Conversion Rate (CR) x Shopping cart
If the equation (2) is adapted for visits, we obtain the following expression:
Visits = Sales/(Shopping cart x CR)
If equation (3) is used in equation (1), the following budget determination is obtained:
Budget = [Sales/(Shopping cart x CR)] x CPC.
An example shows the result of this equation:
From this, a necessary Adwords budget of 5,000 € arises (which with sales of 10,000 € does not seem very efficient). To determine the influence of the shopping cart on the budget, the deduction following the shopping cart can be portrayed. This is as follows:
This means that an increase in the shopping cart of one unit will lead to a disproportionate decrease in the budget. If, in our example, the shopping cart of 50 € is increased to 51 €, the budget is no longer 5,000 € but 4,902 €.
In this example, the positive influence of the shopping cart value to the shop income is clear. By implication, this also means that paid-for advertising first comes into use where it is particularly effective. While the conversion rate is frequently similar for many products and categories, the shopping cart value is more strongly dependent on individual items and possible complements. Consequently, it makes sense to structure or to prioritize paid-for advertising toward achievable shopping cart values.
It is therefore clear that customer shopping cart value is a great lever for making your shop more successful. When optimizing shopping carts, it is first important to determine how value is needed to make your online shop profitable. As shown, this target value can be easily determined for the shopping cart value. Not so easy is increasing the shopping cart value, because this depends strongly on the competitive situation. Measures to increase it are to be found in the shop itself and are described with the terms cross-selling and upselling. But online marketing, i.e. greater reach, can also help achieve better shopping carts. In addition to carefully crafting display texts and meta descriptions, a focus on Adwords budgets for products with high shopping cart values can bring great results.
Published on 03/17/2017 by Dominik Große Holtforth.
Prof. Dr. Dominik Große Holtforth teaches business studies and media management at Fresenius University of Applied Sciences in Cologne. He is also head of the e-Commerce department which deals with strategy-related questions, the controlling of key performance indicators as well as competition strategies in online marketing and e-Commerce. Prof. Große Holtforth is co-founder of the e-Commerce agency Warenkorb.com and founder of the online plant shop “Meine Orangerie.” This is how he combines scientific expertise and practical experience.
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