Research methodology
AWG — Data Insight

1. The rating participants

The rating includes the largest Russian online and offline retailers of tangible goods. The size of a participant is calculated based on total turnover (in rubles) in 2020, according to published data and expert assessments made by the rating developers

2. Definition of the omni-channel performance rating through the eyes of the customer

The omni-channel performance rating assesses how seamless the customer experience is in terms of switching between the purchase channels, e.g., a brick-and-mortar store, a website, a mobile app or a customer support personnel (call center, etc.). Since omni-channel performance is based on two main sales scenarios, i.e. on the regular brick-and-mortar sales and the online sales, where the latter scenario is new for most retailers, the online channel maturity plays a key role in the assessment. The rating considers the following parameters:

  1. the integrated index for online sales, based on a weighted assessment of online sales volume and dynamics;
  2. the integrated customer experience metrics that indicate if and to what extent the online or offline ordering process is seamless, a unified loyalty program is available, the personnel is aware of the store's omni-channel features, the product information is available online and the purchases can be made offline without having to involve sales people;
  3. the integrated interaction with technology metrics designed to assess how advanced the online sales technologies are. The metrics include the website quality, response time, and overall performance, the mobile apps quality and functionality, and the role of SMM in sales;
  4. the integrated order delivery metrics that describe the relevant customer experience. These metrics include the diversity of delivery options, the order tracking option, the quality features of delivered goods, and the convenience of the door-to-door delivery in terms of available delivery windows. The metrics also show if the order processing complies with the claimed benchmarks.
The rating does not assess internal processes of stores, such as their CRM, fulfillment processes, call center automation, etc., as they are hidden from the customer. The analysis included only those metrics that reflect the quality of retail customer experience.
The rating does not analyze quality, i.e. biased features. For that reason, the design, the website and app usability, offline and online order convenience and so on were not assessed. The only quality feature assessed was how helpful and informative the sales people were.
A detailed list of metrics is given below.

3. Rating criteria

The rating is calculated by summing up all metrics. Each metric is scored on a two-point scale (from 0 to 2, with an accuracy of 0.1). All metrics have equal weight in the total score.

4. Objective and subjective assessment factors

The rating authors did their best to ensure each measurement to be highly objective by re-checking the results, cutting off inconsistent values, and using other controls . However, the very title of the rating — "through the eyes of the customer" — implies some bias as customer experience may vary between individuals.

5. Participation criteria

  1. The rating includes the largest retailers in Russia by total turnover in 2020 with well-established offline and online sales channels.
  2. Pure online players are not included in the rating as the omni-channel criteria were not applicable to them during the research (e.g.,
  3. The rating does not include offline players whose online solutions provide no option to order online.
  4. Major offline and online players (Ozon, Lamoda, etc.) are not included in the rating since only one of their sales channels, i.e. either offline or online, was explicitly well established at the time of the research and rating preparation (up to September 2021).
  5. The rating does not include companies that use or have previously used sales via distributors (e.g., Oriflame) because the research methods are not fully applicable to this online sales model.
  6. The public rating includes 100 companies that ranked the highest. However, the study authors analyzed more companies matching the above participation criteria.

6. Sources of data and estimates

The rating authors used:

  1. the online stores' data on delivery options, number and types of pickup locations, product details on the website, and online sales volumes;
  2. AWG and Data Insight estimates based on accumulated data and/or findings of proprietary technology solutions;
  3. the data obtained using the "mystery shopper" technique that shows which loyalty program features are available, if online and offline orders are coherent, the sales people give quick and informative responses, and the delivery has any features;
  4. the data on the mobile app ratings and number of downloads as well as downtime and performance of the participants' websites derived from third-party services.
To ensure the confidentiality of interaction with market participants, the companies do not always disclose their data sources.
The "mystery shopper" technique included offline and online test orders as well as obtaining and evaluating information from the store personnel. High-demand products with standard delivery terms were selected for the test orders. The technique ruled out ordering oversized goods and express delivery.

7. General principles

  1. The rating includes scores relevant at the time of publication and based on an optimal combination of currently available methods and data. AWG and Data Insight do their best to ensure the highest possible accuracy of the rating and the score consistency for all participants.
  2. However, the rating may be somewhat incomplete or inaccurate as the transparency of the researched market is limited, and the participants use different business models. AWG and Data Insight may not be held responsible for any adverse consequences associated with any company's inclusion or non-inclusion in the rating or the discrepancy between the rating scores and actual data.
  3. After the rating publication on, its participants, ranking order and quantitative data that may affect the order cannot be edited, regardless of any new data received.
  4. In future studies, AWG and Data Insight may publish scores that differ from the current rating scores of the same participants. It may happen due to other methods and definitions used in such studies or new data gathered between the publication date of this rating and that of any future study.
Omni-channel performance rating metrics
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