In anticipation of his upcoming conference presentation, Pizza Analytics & Optimization, at 
Predictive Analytics World San Francisco, March 29-April 2, 2015, we asked Mohamad Khatib, Sr. Project Manager at Nielsen, a few questions about his work in predictive analytics.
Q: In your work with predictive analytics, what behavior do your models predict?
A: The work I have done focused on predicting customer purchases, in response to targeted advertisements and marketing promotional offerings. The aim is to help manufacturers optimize their product marketing promotional spend by predicting customer responses to different promotions.
Q: How does predictive analytics deliver value at your organization? What is one specific way in which it actively drives decisions?
A: By utilizing predictive analytics, the small business we worked with (pizza shop: manufacturer and retailer) were able to better schedule promotional campaigns that will yield the best results, and attract targeted customers.
Having informed predictions enables these pizza outlets to optimize their inventories of promoted products. In addition, they guide production staffing plans so that pizza outlet managers can schedule resources appropriately to meet the changing demands. This will help to ensure effective delivery of these products to clients.
Q: Can you describe a successful result, such as the predictive lift of your model or the ROI of an analytics initiative?
A: By applying predictive analytics, the engaged pizza shops were able to effectively plan for their staffing needs, and align that with targeted promotions carried out to clients.
As predicted, one pizza shop was prepared to respond to increased demand in response to the post card promotions. As responses exceeded initial projected rates in some cases, additional staffing plans were in place to meet the increased demands and carry out the required service levels.
Also, they were able to compare effectiveness of types of promotional campaigns as applied to their targeted demographics.
Q: What surprising discovery have you unearthed in your data?
A: Even though we utilized simplified models to provide predictive analytics, the correlation between promotional activities and client responses was easily visible and measurable. This ease of quantification of results in the pizza business produces great benefits in directing promotional activities to maximize returns on spends.
Q: Sneak preview: Please tell us a take-away that you will provide during your talk at Predictive Analytics World.
A: A simplified predictive analytics model can be easily developed and applied to a small business. Such limited efforts and investment will bring positive returns to manufacturers.
This simplification does not trivialize the approach, and has proven to produce valuable results and insights to predict responses to targeted pizza promotions.
In addition, it is clear that successful deployment of predictive analytics will have cross-functional impact throughout the organization. This impact applies to large as well as small organizations. Respective business processes will be impacted accordingly.
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Don’t miss Mohamad Khatib’s conference presentation, Pizza Analytics & Optimization, at Predictive Analytics World San Francisco, on Wednesday, April 1, 2015 from 10:25-10:45 am. Click here to register for attendance.
