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The company General Fueller has 25 gas stations. The rising price of gasoline and the fierce competition in the gas station market lead to the need to find new ways to compete for customers and improve profit margin.

Business scale and background

The company General Fueller has 25 gas stations. The rising price of gasoline and the fierce competition in the gas station market lead to the need to find new ways to compete for customers and improve profit margin.

Tasks

Ensuring systematic clients return and increased sales of related products through personalized fuel and goods prices

Solution

Integration to the Megainsight platform, which allows to automatically identify the consumption model of each client with the ability to form individual price offers for fuel and goods, both in automatic and manual mode.

Results

783% - ROI from automation of the process of forming personal offers for clients

According to the internal report of customer and the data of Megainsight. For the analysis, we took the indicates from December 2020 to May 2021 inclusive minus the cost of connecting and using the Megainsight platform.

+40%

Net profit increased (25 filling stations)

+30%

Increase in average bill

+4 USD

Increase in marches per ton of fuel

Sergey Balsin

Member of the board

One of the our main task is not to look for additional income only in new clients or products, but to work efficiently with our loyal clients, retain them, find optimal solutions to increase sales to them. But clients are all different, with different wallets and different life needs and behaviors.

Hence, the task is being built - to learn to recognize them and point by point, individually offer them such conditions under which their loyalty and, accordingly, the frequency of purchases or the amount of one-time purchases will grow.

Key cases of platform application in customer

Who is lost

By analyzing client consumption patterns, the company formed parameters for creating target groups of lost or declining-demand clients. The most valuable lost clients were identified based on factors like monthly gas station visits and average bill. For this narrow group, the company sent personalized gasoline offers with coupon conversion rates ranging from 5 to 15% depending on the month.

Who didn't buy

The company formed target groups based on consumption parameters to identify clients who didn't purchase certain goods. Hypothesizing that price-oriented clients bought lower quality products from competitors, the company created coupons with personal prices reduced by 20-30% for those goods. This resulted in up to 30% conversion for certain products and a 25% increase in daily bills, without changing prices for those who already purchased the goods.

Who likes to buy goods

The gas station used the automatic calculation of personalized recommendations for clients, creating a list of popular items with reduced prices. Using machine learning algorithms, each client received a unique list of coupons based on their purchase history and consumption patterns. This resulted in personalized offers for each client, leading to up to 40% increase in conversions.

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What's become available due to Megainsight

Data collection and customer segmentation

Creation of a single place for storing and processing all client data, followed by deduplication and normalization. Convenient interface for forming target customer groups by consumption parameters for a task or hypothesis, depending on the needs of the company.

Target offers and prices

Flexible functionality for creating holding shares in the form of coupons that can be linked both to a specific group of clients and individually to each client, depending on recommendations from machine intelligence.

Improve customer service quality

Providing gas station operators with recommendations on the goods that need to be offered to the client during his identification made it possible to standardize the client service within the entire network.

Branded mobile app for clients

A completely updated mobile application that allows to conduct personal communication with the client and increase his brand loyalty through gamification and personal discounts.

Conversion control

The ability to track key business metrics and their dynamics of changes for each target group of customers formed in the platform.

Hierarchical pricing

Transparent ROI analysis for each price coupon, which allows you to form a client group among those who used it / did not use it for further impact and increase the conversion to sale.

Explore the product that has produced the result

Reco

AI will tell you about the dependence of buyers on the price and what kind of

783% ROI

ROI increase with personalized and automated promo marketing

+30%

Increase in related goods average check

3.5 M USD

Net profit increased (25 filling stations)

26%

Customer return rate

Explore

783% ROI

ROI increase with personalized and automated promo marketing

3.5 M USD

Net profit increased (25 filling stations)

+30%

Increase in related goods average check

26%

Customer return rate

RozaMira gas stations increased fuel realization up to 26% by clients who have falling demand

+40%

Ensuring customer return

783%

ROI increase

30%

Increase in average bill

Increase in marches per ton of fuel

+4 USD

Resource-Oil fuel chain showed explosive growth of the loyalty program participants

+40%

Ensuring customer return

783%

ROI increase

30%

Increase in average bill

Increase in marches per ton of fuel

+4 USD

General Fuller gas stations (GF) return up to 40% clients due to goods prices

+40%

Ensuring customer return

783%

ROI increase

30%

Increase in average bill

Increase in marches per ton of fuel

+4 USD

General Fuller gas stations (GF) return up to 40% clients due to personal fuel and goods prices

+40%

Ensuring customer return

783%

ROI increase

30%

Increase in average bill

Increase in marches per ton of fuel

+4 USD

General Fuller gas stations (GF) return up to 40% clients due to personal fuel and goods prices

783%

ROI increase

+40%

Ensuring customer return

+30%

Increase in average bill

Increase in marches per ton of fuel

+4 USD

RozaMira gas stations increased fuel realization up

+26%

Increased fuel realization*

+40%

Ensuring customer return

+30%

Increase in average bill

Increased weekly gain of new clients due to the ability to share coupons to friends

in 2 times

Resource-Oil fuel chain showed explosive growth of the loyalty program

+1000

Average week new customers growth

+100%

Average cross-sell growth

Active customers growth among digitized

76%

General Fuller gas stations (GF) return up to 40% clients due to personal fuel and goods prices

783%

ROI increase

+40%

Ensuring customer return

+30%

Increase in average bill

Increase in marches per ton of fuel

+4 USD

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Resource-Oil fuel chain showed explosive growth of the loyalty program participants

Resource-Oil fuel chain showed explosive growth of the loyalty program participants

Business scale and background

Tasks

Solution

Results

Key benefits

Key cases of platform application in customer

Who is lost

Who didn't buy

Who likes to buy goods

What's become available due to Megainsight

Data collection and customer segmentation

Target offers and prices

Improve customer service quality

Branded mobile app for clients

Conversion control

Hierarchical pricing

Explore the product that has produced the result

Reco

Case Studies

Request a Demo

Your message is sent