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Prescriptive Analytics Use Cases for Sales and Marketing

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But how can sales and marketing leverage the power of prescriptive analytics to maximize the return of their investments in big data and predictive?   

To find out, I interviewed three River Logic veterans about how they have personally helped companies with their retail planning process, CPG, shipping and elsewhere apply the River Logic platform to sales and marketing.  Here’s what I learned.

Leveraging Prescriptive Analytics for Sales and Marketing

Trade Promotion Optimization (TPO) 

In CPG (or FMCG), River Logic is used to optimize trade promotion campaigns.  

Trade promotions are typically done on a weekly basis looking a year out. River Logic helps determine which campaigns to run, and for which products, by various dimensions including retailers and channels.  

River Logic considers different objective functions like revenue, profit, and volume, all depending on the strategic goals and lifecycle stage of a specific product.  For example, a company may have products that are cash cows where profit is the focus.  Or it may have new product introductions where volume and market share are the key objectives.   

Business constraints include promotional budgets (hard number or live accrual), min/max frequency, min pre/post promotional gap, blackout weeks, must have weeks, products to promote/do not promote together, forward buys, etc. 

A TPO-like model can also be applied to retailers where instead of looking within a manufacturer, it optimizes the target promotions within a category.  Of course, with the power and flexibility of the River Logic platform, both manufacturer and retailer could be modeled together which would make for interesting game theory.

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Product Assortment Optimization 

In retail, River Logic has been used to support product assortment optimization. In one example, a telecom provider looked at the assortment of products in their retail stores.  River Logic helped their business users determine the optimal configuration of premium, high end, medium and low price tablets and phones that maximize the total value to the company.   

The model considered:

  • cost of the devices
  • baseline demand
  • substitution effects (i.e., if I have Product A, what does it do to demand for Product B? or conversely if I don’t have Product A, how many customers buy other products vs. leave the store?)
  • sales associate training
  • other costs per product line
  • subsidies
  • average lifetime contribution from phone plans
  • min/max and total number of handsets per category

The model also supported portfolio management, i.e., when to introduce a new phone, eliminate old ones, etc.  Optimization for product assortment and portfolio management can address almost any category in retail, including more complicated SKUs to account for lifetime value and subsidies. One example of this is grocery store produce, which has a limited shelf life.  

Price Optimization 

Associated with assortment but not quite the same, price optimization can be used to determine the optimal baseline price for an item within a category.  The detailed unit costing and opportunity values in the River Logic platform gives clear indicators of potential sources of missed opportunity and how to set prices to assure profitability. Elasticity curves by category are considered similar to the assortment example, including how these curves shift when prices of products that can be regarded as substitutes change.  

Marketing Mix Optimization

Similarly, River Logic can be used for marketing mix modeling.  For example, optimizing the mix of paid advertising across channels such as Google AdWords, Facebook, Twitter, LinkedIn, into different audiences, with different messages.  Since these channels each report on cost per click/impression over time, that data can be leveraged in a manufacturing paradigm as a resource with a specific variable cost and yield (clicks) over time. A good marketer will understand how those clicks translate into revenue which ultimately allows River Logic to optimize the spend to maximize the revenue.

Customer (and Vendor) Contract Negotiation 

The same analysis used for producing the baseline product pricing can be leveraged for contract negotiations with customers and suppliers. The platform’s detailed unit costing and opportunity values can be applied to more than just products or resources. These compelling capabilities can be done by supplier, by customer, by channel, by region, etc.   

When examined by customer, River Logic users have found that the true cost-to-serve some of their most strategic customers resulted in limited or negative profitability. Customer rationalization analysis becomes a very powerful contract negotiation tool. The same analysis when applied to vendors often helps generate more win-win negotiations by identifying terms that would have the highest impact on company profitability with a low impact on supplier cost. 

Why River Logic? 

For each of these use cases, software companies have created packaged applications to address these challenges, so why consider River Logic? 

Package apps support pin-point solutions very well with lots of predefined inputs, interfaces, reports, etc. However, if you are looking to these capabilities as a system of innovation or differentiation for your company to get ahead and outperform the competition, the limitations of packaged apps should be considered, namely: 

  • With packaged apps, your valuable IP and innovation is shared with the vendor or systems integrator.  Once your IP is put into the product, it becomes available to all of your competitors. 
  • Related to the above, you must rely on the vendor roadmap or spend a lot of money and time with a systems integrator.  Many projects fail when companies try to configure packaged apps to do things that they weren’t originally designed to do. 
  • There are limited economies of scale with a packaged app as you need one for every silo problem, so it’s ultimately less efficient, and in smaller companies, it will be difficult for users to develop deep expertise on every packaged app.
  • It is essential to consider that an initial problem representation may eventually prove inadequate and the solution must be expanded to include other parts of the business, which often proves difficult with a packaged app built-for-purpose.  For example, in CPG, companies may want to extend the model to include inventory management positions, cost of goods or production. In retail, a company might want to expand promotions or pricing to reflect supplier contracts, seasonality, or special discounting.

In contrast, River Logic models can be configured to support the exact company need, supporting multiple types of problems as well or better than packaged apps. The company has all the ability in the world to control their innovation roadmap and gain economies of scale without waiting on a vendor roadmap or the systems integrator to change or customize any code. 

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