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IBM chicken dinners for sale!

August 18, 2014

Need to sell more products? Dump Steve, the guy in the chicken suit flagging down customers in the parking lot, and adopt real-time actionable insight. IBM’s four pillar strategy (Sense, Orient, Decide and Act) will turn your big data into action. In our five-part series, we will introduce real-time actionable insight and explore each pillar in detail.    

Gaining the competitive advantage

Competition among grocery stores (and pretty much every other business, industry-wide, from healthcare to energy to financial services) has never been fiercer. For example, high-end grocers are now selling high-quality gourmet meals to-go and providing luxury shopping experiences: you can now procure a personalized list, hire a personal shopper or even phone in your order to be picked up at your convenience. But it’s not just the high end that is pressing—competition from bare-bone budget stores is also increasing.

With very slim margins, organizations are looking for answers. They need to find new markets fast and act on insight to sell more products and services, and to keep clients coming back.

The market of one

IBM’s brand of gourmet meal includes a side of streaming analytics, context accumulation, predictive and prescriptive models plus decision management to move you from mass marketing to careful targeting in the market of one.

Don’t worry, if you don’t have gourmet chicken dinners to sell, IBM can still help.

Respond in a meaningful way with automated business processes, better agility and improved decision making

chicken suit with food.jpgLet’s walk through an example of how a retail store can transform their business using real-time actionable insight. In the era of big data, grocers need to identify when customers are passing by and perhaps in need of a meal. These “in-range” customers would be missed using traditional marketing and decision management. Forget the chicken suit, shift to right-time offers in the business moment.

Devices generate a “stream” of data including time and geospatial location. This data can be combined with behavioral models, context and business processes to deliver real-time actionable insight. Using this insight, a grocer can send a marketing offer (“20 percent off chicken dinner!”) to a hungry customer as he is walking near the store around dinner time. 

Understandably, our grocer has questions. These include:

  • Who to send targeted coupons to?
  • How much potential value do “in-range” customers represent?
  • What is the ideal coupon to send?

IBM solutions make it easy to answer these questions. Natural language processing rules are simple to create and understand. Backing these rules are sophisticated analytic toolkits optimized for streaming data types such as geo-spatial analysis. Big data analytics can preprocess streaming data (normalize and cleanse) from sources such as car sensors or twitter feeds and makes sense of the data in real-time.

Based on analytic results, new business applications emerge such as “in-range” marketing coupons for customers nearby. To ensure the best offer, IBM solutions build rich context and predictive models into decision making. We take frequency of visit, identity, past purchase history and the time of day into account to deliver the best offer. For example, we don’t want to send a coupon for coffee and donuts to the customer if it’s dinner time.

In addition, the gourmet grocer wants to expand the sale and maximize revenue to business partners in the area. If it’s a Friday night, the customer may like to have a bottle of wine and a movie to go with his chicken dinner, so a partnership with the movie rental stand outside and the wine and spirits shop next store would be logical.

Real-time actionable insight for your business

Real-time actionable insight helps organizations optimize decisions and implement repeatable business outcomes across all data, systems, policies and processes. It uses context accumulation as well as real-time and predictive analytics to detect business opportunities across a broader spectrum of interest, providing the appropriate platform and integration capabilities to enable rapid and repeatable execution across big data, mobile applications and cloud environments.

So what do you think: an improvement from Steve in the chicken suit, right?

Join us next week to explore the first of the four pillars of real-time actionable insight, Sense: the ability to better understand something by taking into account the things around it, dynamically, in real-time.

Can't wait for next week? Join the conversation on social using #IBMchickendinner and enjoy these related links: