HOW TO CHALLENGE E-COMMERCE TOPLINE GROWTH, DIGITAL KPIs AND CUSTOMER ECONOMICS TO PREDICT REVENUE TRAJECTORY OF YOUR BUSINESS?

E-commerce is transforming business and private life across the globe, shifting the purchasing behavior online, driven mainly by technological advancements (like improved internet connectivity) and rising digital maturity of market participants.

The last 18 months have shown outstanding market dynamics for e-commerce. Digital KPIs have significantly improved and we have seen outstanding valuation levels of recent e-commerce transactions. Examples are the sale of Perfect Drive Sports Group from Afinum to Bregal, the leading golf e-commerce player in Europe, or MEGABAD (sold to FSN Capital), the leading and fast-growing online retailer of bathroom and sanitary products in Germany, offering a broad portfolio of >340 own and leading branded products. Bike24, the leading European bike and sports e-commerce company, with the broadest bike offering focused on the premium segment did an IPO of EUR 662m on the Frankfurt Stock Exchange.

Global e-commerce has grown at an average rate of around +20% a year pre-COVID-19, reaching around 14.1% of the total retail trade in 2019 and still shows significant potential to advance in the future. The global COVID-19 pandemic acted as a catalyst and accelerated online penetration rates across all product categories, thereby, speeding up the shift to e-commerce by approximately half a decade.

The rise of e-commerce allows businesses to access vast amounts of customer data. Businesses can track the source of website session and conversions into actual orders. They can follow customer cohorts over time and trace the development of new and repeat customers. Besides helping businesses to increase operational efficiencies, this data allows businesses to challenge and improve their topline growth.

FOUR STEPS TO CHALLENGE TOPLINE GROWTH

There are four main steps to challenge topline growth with digital KPIs and customer economics:

STEP 1: TOP-DOWN MARKET MODEL, GOOGLE SEARCHES AND ONLINE MENTIONS

The size and development of the relevant market of an e-commerce business (incl. online penetration rate), derived from a top-down market model, can be better understood by leveraging bottom-up data related to end-consumers’ Google search behavior for relevant keywords and online mentions.

STEP 2: WEBSITE SESSIONS

The number of website session (number of visits to a website) is a central KPI at the beginning of the e-commerce sales funnel and a key driver of e-commerce revenue.?

STEP 3: CONVERSION RATE AND AVERAGE ORDER VALUE

Conversion rate (share of website sessions converting into online orders) and average order value (price per order) are two important digital KPIs that allow for the transformation of website sessions into orders and revenue. Thus, they are important parts of challenging the topline growth trajectory of e-commerce businesses.

?STEP 4: DIGITAL KPIS AND CUSTOMER ECONOMICS

Challenging the topline growth does not end once an order is completed in the e-commerce sales funnel (step 2-3), but should be complemented with a cohort analysis to bring transparency into the development of new and repeat customers across cohorts and over time. This can be done by anchoring the number of orders with the average order per customer across each cohort.

In the following sections, these four steps will be further explained.

1. TOP-DOWN MARKET MODEL, GOOGLE SEARCHES AND ONLINE MENTIONS

The baseline organic growth of an e-commerce business depends on the market development of the segment in which it operates and the importance of marketplaces. Most e-commerce businesses benefit from a surge in the online penetration of their segment. This development is often derived from a top-down market model, split by offline and online share. However, it is possible to take this analysis further and challenge the top-down market model with bottom-up data of end-consumers’ Google search behavior and online mentions. This provides two additional angles of measuring the market development of an e-commerce business, with reliable and up-to-date monthly data.

1.1. GOOGLE SEARCHES - DIGITAL CONSUMER INTEREST

Despite a growing number of customers starting their journey on marketplaces like Amazon, Google remains the dominant place to search for information and products, which is reflected in its over 5.6bn daily searches[4]. E-commerce businesses can leverage the information of Google searches aggregated over time. This can be done by analyzing the search development for a set of relevant keywords to identify trends in customers’ search behavior.

Google searches contain information regarding the digital market development, which is valuable when challenging topline growth. Revenue generated online (e.g. through e-commerce websites) is often highly correlated with the relevant Google search volume. For instance, the revenue of five European e-commerce businesses shows a positive correlation coefficient (p), ranging between +0.459 and +0.924. Thus, the Google search volume development can be considered as a very good indicator of the development of the underlying market.?

Google searches also yield insights beyond overall market development. The Google search volume development can be analyzed across splits such as product categories, brands, and conversion probability. This allows for a deeper understanding of the performance for specific market segments, tailor-made to a specific industry. For instance, the development of Google searches can be clustered into relevant product categories such as tennis rackets and tennis balls for an online tennis retailer or dog food and cat food for an online pet food retailer.

Similarly, searches directly relating to a business or brand (i.e. branded search) can be benchmarked to a specific set of competitors’ branded searches to analyze its relevant performance. Moreover, the Google search volume can be analyzed on a monthly basis. This granularity in the data provides valuable information regarding the seasonality in a market as well as up-to-date data during special events such as the COVID-19 pandemic.

In some industries, it is difficult to find reliable sources for the historical market development. Sometimes, the top-down market model does not fully represent the relevant market of an e-commerce business. Occasionally, it even misrepresents the actual development. For instance, data gathered by a specialized market research provider might only consider the offline segment, ignoring e-commerce. This can occur when a provider has not updated their market sizing methodology in a long time. When e-commerce development is not properly factored in, a misleading picture of the actual market development can result. This in turn can adversely influence the purchasing decision of potential investors.

In such cases, Google searches offer an alternative view on the market development. For instance, the revenue of an e-commerce business might have a much higher correlation with Google searches than the market development derived from the top-down market model. The positive correlation can be explained by the large portion of revenue coming from e-commerce (reading example: 85%). On the other hand, the slow growth from the top-down market model can be explained by the neglection of online retailers within the data, making Google searches the better indicator of the market development.?

1.2. ONLINE MENTIONS

Social media has changed the world over the past two decades, from MySpace achieving 1m active users in 2004, arguably the beginning of mainstream social media, to Facebook’s 2.8bn active users in 2020. E-commerce businesses can analyze online mentions (posted content in online channels containing a predefined set of keywords) systematically over time, also referred to as “social listening”. This analysis can be conducted through an AI-based software in order to uncover meaningful customer insights from conversational data, allowing for strategic business conclusions.?

Like Google searches, online mentions contain insightful end-consumer information that can be used to challenge development trends from a top-down market model and can be analyzed with a similar granularity as Google searches. This allows for two additional angles of measuring the market growth, with reliable and recent data.

2. WEBSITE SESSIONS

Website sessions are a central digital KPI in the beginning of the e-commerce sales funnel and a key driver of e-commerce businesses’ topline growth. With the ongoing shift in customers’ purchasing behavior, the demand for e-commerce is on the rise. The challenge is to capture this demand and attract customers to the website.

Generally, the website sessions are derived from six main customer acquisition channels:

Paid search – people entering the website as a result of paid search campaigns (e.g. google search ads, remarketing)

Organic search – people entering the website as a result of unpaid (or “organic”) search results

Direct – people already aware of the e-commerce business, entering the website by directly typing the domain (URL)

Affiliate – people entering the website through another company’s affiliate link (e.g. blog, YouTube) where the website is promoted

Social – people entering the website through social media channels (e.g. organic posts, ads)

Email – people entering the website through links included in email marketing (e.g. newsletters), often as part of customer retention strategies

The historical development of website sessions across these six customer acquisition channels gives insights into the performance of different session-generating initiatives. Leading e-commerce businesses track and monitor this development closely in order to evaluate and steer different campaigns to ensure high performance and return on investment.?

Now that the historical performance of website sessions across the different customer acquisition channels is fully understood, the topline growth can be challenged. In doing so, an e-commerce business needs to consider whether the current source of website sessions is optimally distributed across channels or if some are overrepresented or neglected. Here, it is important to evaluate the potential of entering new channels as well as enforcing existing ones. Due to the dynamic nature of e-commerce – for instance, the current trend of blending digital payments, social media, short-form videos and live stream influencers – even the most advanced players need to constantly improve their channel mix to stay ahead of competition.

The topline growth of e-commerce businesses can be challenged through a forecasting exercise of website sessions across the six different customer acquisition channels:

Paid search – can be forecasted based on planned ads spend and estimated impact of identified improvements within the current setup (e.g. ad groups, quality score, ad formats)

Organic search – can be forecasted based on the development of Google searches (see chapter 1.1.) and the expectation of exceeding / falling behind this trend, derived from planned search engine optimization (e.g. technical, structure, backlinks, content)

Direct – can be forecasted based on branded Google searches, representing the development of brand awareness (direct website session indirectly benefits from other digital marketing initiatives)

Affiliate – can be forecasted based on historical affiliate revenue (excl. commission), quality of affiliates and planned investments

Social – can be forecasted based on planned budgets derived from the estimated impact of expanding into new channels (e.g. Pinterest, TikTok) and improvements in existing channels (e.g. consistent corporate identity, high quality images and text)

Email – can be forecasted based on the existing email base and the estimated impact of further improvements (e.g. advanced segmentation, new formats, engaging and high quality content, mobile optimized)

Based on the forecasted website sessions across the six different customer acquisition channels and factoring in expectations for future conversion rates and average order values, e-commerce businesses can challenge their topline growth.

3. CONVERSION RATE AND AVERAGE ORDER VALUE

The conversion rate (share of website sessions converting into online orders) and average order value (price per order) are two important digital KPIs for challenging topline growth, as they transform website sessions into concrete orders and revenue.

3.1. CONVERSION RATE

With businesses transitioning towards digital channels, the user experience (UX) and the user interface (UI) on websites have become increasingly significant. For e-commerce businesses, this matters because great UX and UI increase the share of website sessions that convert into customers without having to invest into generating more website traffic. Thus, they increase overall profitability.

The conversion rate should be monitored regularly to allow the effects of specific conversion rate optimizations (e.g. A/B testing, response tracking, and audience testing) to be measured and steered. To challenge topline growth, the forecasted conversion rate should be evaluated based on expected investments vs. past implementations. This should be benchmarked against competitors to evaluate current performance and identify further upside potential.?

3.2. AVERAGE ORDER VALUE

As is the case with conversion rate optimization, an increase in average order value will increase the overall profitability of the business, without investing more into traffic generation. Prices are often dictated by a range of factors such as competitive intensity, brand loyalty, or product type. Nonetheless, businesses can employ general average order value optimizations such as upselling, cross-selling, product bundling and / or free shipping. Occasionally, online retailers are willing to reduce the average order value to promote own brands in order to improve their margins. These are important aspects to consider when challenging topline growth of e-commerce businesses.

4. DIGITAL KPIS AND CUSTOMER ECONOMICS

Challenging topline growth does not end with the successful online sale. Adding the perspective of customer economics allows for a deeper and extended understanding of the customer base. This perspective includes, among other things, analyzing repeat purchasing behavior, customer churn and returns.

While digital KPIs are procured from Google Analytics, customer economics are usually extracted directly from a business intelligence, ERP or CRM system. The two data sources can be harmonized by anchoring the number of orders per customers across each cohort.

Analyzing customer economics sheds light on customer acquisitions and retention performance. This can be illustrated by a cohort analysis wherein customers are grouped into annual cohorts based on the year of their first purchase at the e-commerce business. This view allows to analyze retention behavior along the lifetime of a cohort as well as improvements across different cohorts. Two useful metrics to review in this context are the share of customers returning after the first year and the overall share of revenue coming from repeat customers. Those provide valuable insights into the sustainability of a business and cannot be captured in a mere static analysis.

In combination with the forecasted digital KPIs – website session (read more: chapter 2.), conversion rate and average order value (read more: chapter 3.) – the growth per cohort can be forecasted in order to further challenge the topline growth of the e-commerce business. This can be done by considering existing and planned retention initiatives (e.g. CRM initiatives, email and newsletter personalization, abandoned-cart campaigns, loyalty club) and estimating their expected impact on repeat customer behavior. These initiatives are expected to increase loyalty among the existing customer base and decrease churn, representing an attractive growth strategy that increases recurring revenue going forward, and thus, improves the customer lifetime value.

In conclusion, e-commerce businesses can challenge their topline growth projections using digital KPIs and customer economics and thereby improve forecasting accuracy and understanding of the future revenue trajectory. Moreover, the expected topline growth can be broken down and understood both from the angle of the digital KPIs and that of customer economics.

To find out more about how e-commerce businesses can leverage valuable customer data to better forecast topline growth, please reach out to:

Dr. Stefan Sambol – Managing Partner; [email protected]