E-commerce success story

Case study - Highly Effective Strategy to Increase E-commerce sales by 284% year to year.

We present a case study from 3 years of systematic work in an e-commerce store, showing the increase in revenue and profit as well as the expansion of sales into 5 new markets.

Desportivo is a shop that supplies sportswear. The store focuses on a selected range of good quality products, which are fashionable and willingly bought. Desportivo is also an official distributor of Alpinus - a legendary outdoor brand.

The goals

  • Delivery and automatic calculation of data about the current level of ERS net (effective revenue share net) for a single product or category,
  • Designation of maximum ERS net level, to create a safety brake on marketing expenses,
  • Achieving maximum revenue growth while maintaining the ERS net level (cost-to-turnover ratio),
  • Integration of returns and net margin with the ERP system,
  • The use of profit and margin in the purchase of media in the Google Ads channel (bidding).

The results

  • Creation of a data warehouse and automation of the analysis to create a process for taking fast business decisions
  • Reaching the net ERS level on a scale of 3 years, well below the designated value,
  • Revenue increased in year 1 by 284%,
  • Revenue increased in year 2 by 28%
  • Revenue increased in year 3 by 63%, where 63% of revenue was a few million additional revenue,
  • Revenue increased in year 3 by 94% with foreign markets taken into account.
Increase revenue at the turn of 3 years
Our process

A good strategy is the key to success

From the beginning, the key issue was to set clear goals and select appropriate metrics. It was important to maximize revenue, which was related to an aggressive increase in advertising spending on the one hand, while on the other hand, it was also momentous to maintain the margin of profitability. The advertising budget cannot exist indefinitely without control and clear boundaries, however, it is possible to agree that the budget is unlimited with the adoption of certain indicators.

The store decided to build a data warehouse and use it to develop a marketing strategy. The warehouse was built on the Google Cloud Platform (GCP) using the WitCloud tool which again uses (GCP modules not just to collect and combine data, but also for communication between the data warehouse and the Google Ads system. (actions based on analytics directly taken on Advertising account)

Implementation

The first point was to make all the data consistent with net worth. This allows us to take an accounting-like approach and calculate indicators correctly.

After all, data was made consistent with the net costs, the cost attribution was made to assign expenses to each category and product available in the store. Using data from the Google Analytics e-commerce module (revenue from product/category) and information about expenses (attribution in WitCloud) we have full data to use the ERS formula.

The calculation of the ERS net for the e-commerce category controls keeping profitability in check, where the level of this indicator is our safety brake for budget spend. For example, 10% net ERS can be compared to subtracting 10% from the margin. If the net margin is 40% and the net ERS is 41%, we are in the red by 1%.

We do our best to ensure that each e-commerce category does not exceed the set maximum percentage of ERS. On the other hand, when some e-commerce categories achieved a low ERS well below the established threshold, campaigns within the profitable category were maximized. This made the level of budget irrelevant and highly elastic, it was maximized within the desired level which allowed for profitable and aggressive scaling.

Cloud Tech Role

Net values are one of the arguments for which it was necessary to create a data warehouse in order to be able to perform mathematical operations on a specific schedule, including:

  • Converting the values of the product/category from gross to net,

  • Calculation of the net cost of delivery,

  • Taking into account different rates of VAT in a given country and conversion to net value,

  • Inclusion of a margin.

You can read more about the net worth here in this article

On the other hand, data attribution was used in an unusual way. Attribution was not used to analyze which marketing channel is better at starting or closing sales. However, cloud tech and attribution were used to assign the cost to the user's session (the user's travel on the website). To put it simply, if the user was browsing categories A and B, 1 PLN spent on advertising was assigned 50% to category A and 50% to category B. Thanks to this, Cloud tech and the WitCloud tool were used to determine the expenses for categories and products, which was the essence of the strategy and the ERS calculation for the store category.

Further plans for Cloud technology and WitCloud

To sum up; the first thing that arises is the question, "Is even more possible after such spectacular increases?" In the case study, we mentioned the integration of the customer's margin and ERP system for a reason. The ERP system has the stock data and prices of the products from suppliers. It turns out that when comparing the net ERS with the margin of the product or category, the safety brake was not always well-defined.

Some categories with a higher margin may have a higher ERS level, which seems obvious, but often the obvious conclusions do not come easily. It is an intangible value that came from a data warehouse, which can be called business know-how. In a word, it is real-time knowledge (in advertising systems and in automated reporting), which gives information on which category to maximize, when to do it, and how to safely increase income (managing the campaign structure adapted to the available data). 

On the other hand, the Cloud technology was integrated with the Google Ads system and the margin was imported to the system, instead of net revenues. In the reporting area, it is possible to set a better and more accurate safety brake, while in the purchasing sphere, we can provide Google's smart shopping or smart bidding 2.0 mechanisms with better data to maximize the margin, directly in the advertising system.

Currently, there are more and more mechanisms in Google Ads that are operated by machine methods, taking the strain off human resources and generating better results than humans. The key issue seems to be supplying these mechanisms with better data because other elements are less and less influenced by specialists.


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