Channel Collaboration

Can you predict the future?

consumer demand

Consumer demand in a world of uncertainty

The upsets and unpredictability of global political events such as the Brexit vote or the election of Donald Trump got me thinking about the famous quote of U.S. politician Tip O’Neil that “all politics is local.” Upon further reflection, you could replace the word “politics” with a number of other things including “consumer demand,” since purchase decisions are driven by many factors including local conditions.

Recently I was talking to an IBM colleague about her drive to a client outside Philadelphia; the roads in the eastern suburbs where she lived were a snowy and icy mess while the roads in the western suburbs were nice and dry. Clearly, a weather forecast for “Philadelphia” would not have recognized these differences. And there surely were impacts to consumers’ shopping plans based on their local market conditions. Add to the weather other conditions such as road construction and sporting events, and we find that the drivers of consumer demand are very complicated and much broader than the traditional activities of advertising and trade promotion.

Get local in demand prediction

The ability to collect, manage and analyze all the data that drives consumer demand historically has either been unavailable or the technology to process it beyond the reach of CPG companies. But recent advancements in data curation, data management, analytics processing and most importantly cognitive technology have opened the doors for a new set of capabilities to drive insights and performance at the local level.

For example, a leading food and beverage company can identify, predict and act upon demand drivers related to weather and local community event data (e.g., a classic car show or a middle school girls soccer game) at a zip+4 level  — by day and day part – for each of their target consumer segments. This insight is then made actionable with a targeted mobile offer to the right individual consumer, at the right time and place — a new level of precision marketing! This has resulted in substantially improved marketing effectiveness driven by the company’s ability to model and act upon these hyper local external drivers of purchase behavior.

For those companies that can execute in store, DSD distribution models as an example, the ability to use this hyper-local forecast to reduce out of stocks, optimize routes / sales rep in store activities and improve replenishment processes is unprecedented. But even without a store level distribution model, these insights can be used to optimize assortments and other category management analyses.

IBM is marketing this exciting, game changing advanced analytics capability in a solution called Metro Pulse. If you would like to see Metro Pulse in action, please stop by the IBM booth (#1720) at NRF 2017. It is just one of the solutions that will be showcased at the IBM booth — hope to see you there!

Consumer Products Industry Executive Consultant, IBM

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