Weather and Event-aware business intelligence for the optimization of campaigns and resources – old

“Weather and Event-aware BI Sales Strategy Advisor ” is the solution developed by BIG BANG – in collaboration with EW-Shopp –  to enable maximization of marketing budgets and optimization of workforce.

The goal of this new solution is to optimize Salesforce and Marketing communication planning by predicting daily number of visitors. More clear understanding on visitation patterns gives valuable insights for scheduling staff on the floor to match customer demand and improve customer service or at least make it more consistent; improved work organization on the floor and coping with logistics and stock challenges more effectively; maximizing marketing budgets; making more accurate sales predictions.

KEY OBJECTIVES

Key objective is to enable better, faster, informed business decisions through (weekly) salesforce optimization and marketing activities / campaign management optimization by having more clear response to shifting foot traffic patterns.

 

EXPECTED IMPACT

The use of meteorological and event data through Service is expected to enable improvements on more levels:

  • Adapting sales activities on the floor to make them more beneficial (when store managers receive information to anticipate higher foot traffic, salespeople should act for increasing volume – when foot traffic is expected to be lower salespeople should perform activities aimed at increasing closing rate and/or basket value).
  • Giving information to marketing department on ad-hoc marketing activities, i.e. when to enforce »must have« activities vs. »best performing« activities and when to perform activities with brands/distributors.
  • Adjust schedules with stronger sales force presence when higher traffic is expected (predictions for five days in advance also satisfy the legal obligation of changing schedules three days in advance), which also positively affects in better working climate.
  • Improved work organization on the floor and coping with logistics and stock challenges more effectively i.e. adapting delivery times when lower visitation is anticipated. Scheduling staff to match customer demand furthermore positively influences customer service or at least makes it more consistent.
  • More accurate sales realization forecasting, since based on historical data, a high correlation on the level of store traffic – sales performance is noted.

INDUSTRY IMPACTED

  • Retailers in the segment of Consumer Electronics & Home Appliances
  • Brand Manufacturers/Distributors

RESEARCH & INNOVATION DOMAIN: Data integration, data aggregation, analytical and predictive modelling, user interface and visualization

TOOLS INVOLVED:  QMiner, SPSS, MariaDB, MS SQL, QlikSense

CONTACT PERSONPatricija Filipič Orel patricija.orel@bigbang.si