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Customer analysis for Loyalty Programs (Business Intelligence)
Customer analysis for Loyalty Programs (Business Intelligence)
Customer analysis for Loyalty Programs (Business Intelligence)
Customer analysis for Loyalty Programs (Business Intelligence)
Customer analysis for Loyalty Programs (Business Intelligence)
Customer analysis for Loyalty Programs (Business Intelligence)
Customer analysis for Loyalty Programs (Business Intelligence)
Customer analysis for Loyalty Programs (Business Intelligence)
Customer analysis for Loyalty Programs (Business Intelligence)
Customer analysis for Loyalty Programs (Business Intelligence)
Customer analysis for Loyalty Programs (Business Intelligence)
Customer analysis for Loyalty Programs (Business Intelligence)
Customer analysis for Loyalty Programs (Business Intelligence)
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Customer analysis for Loyalty Programs (Business Intelligence)

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High competition in the market causes struggle for every customer. Each retail chain is trying to find a unique way of retaining current customers and attract new ones. Often retailers try to use …

High competition in the market causes struggle for every customer. Each retail chain is trying to find a unique way of retaining current customers and attract new ones. Often retailers try to use Loyalty Programs to motivate customers to make more purchases.
ScienceSoft develops analytic systems that allow retailers to use the full potential of their Loyalty Programs. Through the deep purchase analysis of each customer, the system builds complex behavioral models and identifies trends in customer preferences.

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  • 1. 2014 Customer analysis for Loyalty Programs
  • 2. Loyalty Programs in Retail Loyalty Programs help retailers keep track of their regular customers, as well as increase loyalty to their brand. Almost each Loyalty Program includes discounts and coupons to encourage consumers to buy more. But do they buy and stay loyal? The problem with almost all Loyalty Programs is high cost and no influence on results. We offer the influence.
  • 3. Customer analysis Retailers have to build loyalty keeping in mind customers’ interests, not pushing their interests in the first place. We build loyalty programs taking into account what your customers want and need. And this is possible through deep purchase history analysis and customer attribution.
  • 4. Do you know your customers? 85% of U.S. Consumers prefer personalized offers reflecting previously purchases GROCERIES COSMETICS HOUSEHOLD GOODSCLOTHING & ACCESSORIES 67% 14% 5% 6% Customers want coupons for: 57% signed up for a Loyalty Program to get a discount 81% would not search for promotions on purpose
  • 5. Analyze your customers Mass promotional sales eats up 23-30% of gross margin. Isn’t it reasonable to increase the effectiveness of promotions? Use the full potential of your Loyalty Program by taking advantage of ScienceSoft analytical offering. Through the deep purchase analysis of each customer, the system builds complex behavioral models and identifies trends in customer preferences. Retailer Customer share information
  • 6. Purchase history gathering ScienceSoft develops analytical systems that help integrate and analyze customers’ purchase habits and preferences. For each customer the system collects maximum information including time and place of each purchase, promotional sales, etc. Analysis Higher salesData integrationPurchases
  • 7. Customer analysis The system automatically analyzes data, segments customers, identifies patterns in their purchases, generates forecasts, etc. Model recalculations are carried out on a periodic basis depending on the needs. This allows retailers to monitor changes in preferences of individual customers or customer groups, as well as adjust assortment based on this changes. Data Analysis Understanding
  • 8. Personalized communication Based on analytical and predictive models, the system automatically builds a set of personalized recommendations for each participant of a Loyalty Program. Automatic recommendations take into account not only previous purchases, but also purchases of similar customers. This allows retailers to offer relevant products beyond customer’s usual purchases but at the same time take into account areas of his / her interests. You need Customer needs Your offer
  • 9. Enhanced email and web offers Generated recommendations can be used for personalized e-mail campaigns, enhanced in- store offers and coupon generation. This will make your customers feel special. All participants of a Loyalty Program receive promotional offers and information about products that fit their interests. This helps gradually expand a usual range of each customer’s purchases. Time AggregativeLoyalty Personalization
  • 10. Technologies and tools ScienceSoft has a wide experience in data analysis using a variety of tools and platforms. We do not stick to specific products, but proceed from our customers’ infrastructure and preferences.
  • 11. ScienceSoft in BI and Loyalty  Data analysis for American and European retailers with more than 5.000 stores; world FMCG producers with more than $50 bn turnover  24 years in analytics and prediction algorithm development  CRM development for companies with more than 5 mln clients
  • 12. Key facts about ScienceSoft  Locations in Western and Eastern Europe  400+ full-time staff  ISO 9001:2008 and CMMI best practices  Customers in 25 countries  More than 35 patents in data analysis
  • 13. Thank you! SCIENCESOFT, INC. 2 Bedy Str. 220040 Minsk, Belarus Phone: + 375 17 293 3736 Email: contact@scnsoft.com Web: www.scnsoft.com SCIENCESOFT OY Annankatu 2 A 2 00120 Helsinki, Finland Phone: +358 45 178 4880 Email: contact@scnsoft.fi Web: www.scnsoft.com

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