CLIENTS BASE ANALYTICS
HOW IS IT USEFUL:
increase in the communication act effectiveness (less price for a client), increase of the average check, attracting new target audience groups, at the expense of competitors as well
WHAT WE CAN LEARN:
- Ratio of repeated clients
- Frequency of purchases with registration or hash card
- Shopping basket - breadth, price, seasonal and time features
- Behavioral profiles of buyers - parents, healthy lifestyle, «cook at home»,
- consumers of ready meals, middle class, «digital first», etc. (density and groups determined by the algorithm)
- Estimating the possibility of making purchases in Ecom
- Segmentation by completeness and description of the critical completeness of the basket for customer binding
WHERE TO USE IT:
- Targeted advertising by profile
- Profiles search for surveys
- Targeted offers for the most prospective and interesting purchases
- Capturing customers from competitors on upselling basis to a basket width that is critical for the transition
DETERMINATION OF PRICE AND RANGE COMPETITORS STRATEGIES
HOW IS IT USEFUL:
target audience groups attraction at the expense of competitors, prevention of outflow to competitors, the ability to respond quickly on the actions of competitors and substitutes
WHAT WE CAN LEARN:
- Assortment policy in terms of categories completeness within one type of product category
- Assortment policy of product categories types
- Pricing policies
- Analysis of the most probable basket and average bill for similar customer
- profiles
- Allocation of competitors brands according to selected strategies
WHERE TO USE IT:
- Search for a free niche on the market based on the open data analysis
- Recommendations development for improving the service system (trade equipment, Ecom algorithms, etc.)
- Pricing policy regulation into categories
DETERMINATION OF REASONABLE LOCATIONS FOR POINTS OF SALE
HOW IS IT USEFUL:
optimization of trading platform, maximizing profit from one point of sales and increasing the effectiveness of interaction with partners
WHAT WE CAN LEARN:
- Location of points of sale
- Transport accessibility
- Characteristics of residential properties and the real estate market
- Mobile operations data (possibilities of data purchase
WHERE TO USE IT:
- Identification of optimal locations for opening new offline points of sales
- Determination of the optimal product matrix and a point of sales format
- Building recommendations for attracting relevant to the target audience partners (for example, a pharmacy, zoo corner or a coffee shop)