Research methodology
AWG — Data Insight

1. The participants of the rating:

The rating includes the largest Russian retailers selling tangible goods via online and offline channels. A participant's rating is calculated on the basis of total turnover (in rubles) for the year preceding the study and according to public data, as well as the expert judgment of the rating creators.

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 when switching between such purchase channels as a brick-and-mortar store, a website, a mobile app, or customer support (call center, etc.). Omni-channel performance is based on two main sales scenarios: regular brick-and-mortar sales and online sales—the e-commerce scenario, new for most retailers. Therefore, the maturity of the online channel plays a key role in the assessment. The rating takes into account the following parameters:

  1. the integrated online sales index, based on a weighted assessment of online sales volume and dynamics;
  2. the integrated customer experience metrics, which include: seamless online or offline ordering process, a unified loyalty program, the personnel being aware of the omni-channel capabilities of the store, product information published online, and possibility to buy offline without a sales assistant;
  3. the integrated customer interaction with technology metrics, designed to assess how advanced the online sales technologies are. These metrics include the website quality and load speed, how it handles loads, the quality and functionality of mobile apps, and the role of SMM in sales;
  4. the integrated order delivery metrics that describe the relevant customer experience. These metrics include the variety of delivery methods, the ability to track orders, the quality of goods delivered, and the convenience of door-to-door delivery in terms of available delivery windows. The metrics also indicate whether order fulfillment meets the claimed benchmarks.
The rating does not analyze the stores' internal processes, such as their CRM, fulfillment processes, call center automation, etc., as these are not visible to the customer. The analysis includes only those metrics that reflect the quality of the retail customer interaction.
The rating does not analyze qualitative characteristics, as such an assessment is usually biased. Therefore, design, website and application usability, convenience of offline and online ordering, and similar features are not evaluated. The only parameter that is qualitatively assessed is how helpful shop assistants are.

Refer to the table below for a detailed list of metrics.

3. The criteria of the rating

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

4. Objective and subjective assessment factors

The authors of the rating did their best to make each measurement as objective as possible by double-checking the results, eliminating inconsistent indicators, and applying other control methods. However, the very title of the rating—"through the eyes of the customer"—implies some bias, as the customer experience can vary from person to person.

5. The methods used to select Top-100

  1. The rating includes the largest Russian retailers by total turnover for the past year, 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 at the time of the project (e.g., Ozon.ru).
  3. The rating does not include offline players whose online solutions do not offer the option to order online.
  4. Large 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 certainly well established at the time of the analysis and preparation of the rating (up to September of the previous year).
  5. The rating does not include the companies that use or have used 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 participation criteria mentioned above.

6. Sources of data and estimates

The rating authors use:
  1. the online stores' data on delivery speed and 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 obtained using proprietary technology solutions;
  3. the data acquired using mystery shopping, that indicates which loyalty program features are available, whether online and offline orders are consistent, and whether the shop assistants provide prompt and informative answers;
  4. the data on mobile app ratings and downloads, as well as the downtime and performance of the participants' websites, obtained from third-party services.

To ensure the confidentiality of the interaction with market participants, the companies do not always disclose their data sources.

Mystery shopping included offline and online test orders, as well as obtaining and evaluating information from the store personnel. Popular products with standard delivery terms were selected for the test orders. The technique ruled out ordering large goods and express delivery.

7. General principles

  1. The rating includes the scores relevant at the time of publication that are based on an optimal combination of currently available methods and data. AWG and Data Insight make every effort to ensure the highest possible accuracy of the rating and consistency of scores for all participants.
  2. However, the rating may be somewhat incomplete due to the limited transparency of the assessed market and different business models of the participants. AWG and Data Insight shall not be legally liable for any adverse consequences associated with the inclusion or non-inclusion of any company in the rating or the discrepancy between the rating scores and actual data.
  3. After the rating is published on datainsight.ru and omnirating.ru, 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 ratings for the same online stores that differ from the current ratings. This may be due to different methods and definitions used in such studies, or due to new data accumulated between the publication dates of this rating and another study.

Table. Omni-channel performance rating metrics