Russia’s first study of the use of CJM practices in retail

Russia


IT NewsFacts and forecastsMarket analytics

Ekaterina Alexandrova | 10/16/2020

Russia's first study of the use of CJM practices in retail

The digital marketing laboratory of the IT company “CROC”, the organizers of the specialized conferences Retail TECH and the Digital Leader networking platform in September 2020 conducted a comprehensive study,
dedicated to creating the best customer experience in the retail business “CJM: Retail Treasure Island”.

The authors of the study found out at what stages most companies lose customers, what data helps to assess the level of customer loyalty and how to find ideas for product development and
services. The survey involved both retail experts (FMCG, Fashion, electronics and other segments) and ordinary consumers of the age category from 18 to 55 years old. In total, more than 540 were polled
respondents.

The declining purchasing power and high competition in the market requires retailers to work harder on customer loyalty and retention. Customer Journey Map has become the main tool
retail to solve this problem. The representatives of the companies that took part in the research agreed that the experience of conducting CJM research in Russia is still small in comparison with the international one.
practice (on average, no more than three years), but has great potential. Today 39% of surveyed experts use the CJM tool in retail, another 37% are planning. For comparison: in 2018, 67% of companies
CJM was already used in the world, and the very prototype of CJM appeared in the US retail in the 1930s, when market researchers began to conduct a qualitative study of brand buyers and realized that
demographic factors are insufficient to explain consumer behavior.

Increasing sales, identifying customer churn points and understanding your target audience are the top reasons for using CJM, according to experts. In addition, using this tool, companies
want to reduce customer acquisition costs, improve conversions, and discover growth points for further product development. So, using CJM, experts determined that in the retail market 80%
In some cases, the loss of customers occurs in the process of registering a personal account, filling out forms and choosing a product – the path from the moment the client appears on the site / in the store to the first purchase.

The survey results showed that the starting point for creating a “customer journey” is usually the surveys and research conducted by the business to collect customer data. As a rule, companies
collect information about customers from digital channels: CRM, websites, mobile applications, but some companies also analyze the behavior of visitors in regular stores.

Most often, companies try to find an approach to the client on their own, without resorting to the services of third-party consultants, and use custom development. To this end, many organizations are developing
internal competencies in data analytics and create their own digital services. Unfortunately, this approach leads to a situation where the business lacks knowledge, experience and ready-made effective
tools. 40% of respondents reported that they had mistakes when creating a CJM. Time and resources are often wasted on erroneous actions, especially in terms of collecting, analyzing data and interpreting
results.

CJM research data is most commonly used by marketers, analysts, account teams, product owners and sales teams to improve customer experience and
elimination of problem areas in Customer Journey. A company’s customer experience is usually assessed using conversion metrics and retenshion rate (an indicator that determines the level of loyalty
customers). The survey results showed that in the process of working on a client’s CJM, regularity is important – the more often the metrics are monitored, the more value of the research, the data of which can be
use to increase customer loyalty.


According to experts, CJM can be a valuable business assistant, but for its results to be as effective as possible in developing a customer experience, the retail market needs more practice.
To do this, it is necessary to increase the level of expertise in the market, convey the value of using CJM to company leaders and learn how to use digital tools for analyzing and processing client
data.

“Having become the authors of the first Russian research on CJM, we wanted to draw the attention of business to the importance of systematic approaches in its construction, identified key values ​​and mistakes that are relevant for
Russian retail. Nike is an example of a global brand that works with emotion at every stage of the customer journey, aided by the rich experience of CJM in American retail. Finding that
Customers are interested in the digital experience, and the company was able to sell the limited edition sneakers in less than an hour through the Facebook Messenger AR app. This example demonstrates the difference in
assessing the importance of CJM for working with customer experience (4.5 / 5 in the United States and 3.9 / 5 in Russia). We see that American companies have more practice of working with this tool and therefore more successful cases.
Russian brands are just beginning to get the same opportunities that we talked about in our study, ”said Elena Volkovskaya, Head of the Digital Marketing Laboratory, Director of
strategic marketing of the IT company “CROC”.

retail, tools

KROK | CROC



Yandex has launched a service to control deliveries in retail

Yandex has launched a service to control deliveries in retail


IT NewsBusiness ToolsPurchasing & Logistics

Ekaterina Alexandrova | 09/16/2020

Yandex has launched a service to control deliveries in retail

The logistics platform Yandex.Routing has launched a new service, Delivery Control, which monitors the movement of suppliers’ vehicles in real time.

It is expected that distribution centers of retail chains, warehouses of distributors and darkstores of online stores will become users of the service.

“Supply control” continuously monitors all the suppliers’ vehicles that go to the warehouse, taking into account their geo-position, speed and traffic situation on their way, for example, the prospect of education
traffic jams. For each vehicle, a special algorithm calculates ETA (Estimated Time of Arrival) and collects all data in a single window. This will help logisticians track
the arrival of many vehicles with cargo from different suppliers.

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The service is designed to provide transparency in the supply chain of FMCG manufacturers in order to increase delivery speed and reduce costs. “Delivery control” allows you to identify the cause of the failure, for example
late car or queue for unloading, and promptly eliminate it.

Using the ETA indicator in logistics allows you to optimize transport flows and labor resources. The warehouse knows in advance when and in what volume the order will be ready for unloading, therefore
can reduce delivery downtime losses and balance staffing levels.

Currently, about 10 FMCG manufacturers from the list of major suppliers of retail chains, including Baltika, Kolomensky BKK, Rusagro and Simple Group, operate on the Yandex.Routing platform.
These and other suppliers have already gained the ability to transmit data on the movement of their goods to retail chains and stores. By the end of the year, the company plans to increase the number of people connected to the platform
manufacturers from the FMCG segment to provide a more complete picture of supply to retail chains.

retail, services, warehouses

Yandex | Yandex



How to Build a Retail Startup



I’ve built a demo app called SmartSneaks that lets a user convert a song or image into a generated shoe design! This is an example of how AI can be used to transform retail by giving users a more personalized experience. The tools I used to build this are the Flutter framework for mobile development and the Flask framework for web development. There are 3 learning objectives in this video including how to build a deep learning API for your mobile app, how to generate images with a generative adversarial network, and how to calculate image similarity with OpenCV. I hope you find this demo tutorial useful, enjoy!

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