How to sell Analytics? it is full of bells and whistles to the extent of getting sales professionals trapped into the feature trap. What kind of insight you should give your customers? How do you show your understanding of what analytics does to a customer operation and how much it saves him?

1. Selling analytics requires knowing what they can do to your customers
The silver bullet you were waiting for!
Analytics! great stuff! loads of features, fancy executive charts, etc. But how can you sell it?
and what argument do you use?
Firstly, your customer must have enough data to draw insight from. If he has 10 years’
worth of operational data, he could use Analytics in four ways:
1. Descriptive: to describe what transactions took place, when, by whom, etc. How
many orders were placed by what customer and when? What is the value of each
order? What is the collection record of certain customers? Average deal time, deal
value. It can be used to produce “descriptive” reports to senior management
2. Diagnostics: to diagnose what is wrong. Your customer receives orders from a
certain set of their customers during the first and third quarter. Suddenly, those
orders stop coming in and certain sales departments suffer low revenues. Analytics
diagnoses low revenues problem and highlights the reason to be order pattern
anomaly from those customers. Same goes for unexpected variations in average
order values, order sequence pattern, etc.
3. Predictive: A certain behavior leads to a certain outcome. Customers reduce their
purchase value or timing leads to losing them completely after 2-3 quarters.
Analytics has tons of data to draws insights from, hence it can predict the loss of
certain customers. A pattern of failure or parts replacement takes place that is
usually followed by a complete failure and service outage. Again, analytics links the
parts replacement pattern and alerts, not only maintenance department, but also
production and sales that orders might not be fulfilled because a certain machine
will highly likely fail (to the best knowledge).
4. Prescriptive: This is the apex of analytics. Analytics not only describes what goes on,
nor diagnoses or predicts. It prescribes the cure. It says: I noticed the following:
• Machin ABC represents 25% of your production capability (descriptive)
• When this machine fails, your deliveries and order fulfillment gets delayed
by 2 days on the average to east coast orders and 4 days to west coast
(diagnostics)
• When this machine has consecutive mechanical failure and parts number
356288, 37761, and 997345 are replaced it means that a major failure can be
predicted. This major failure usually leads to lengthy production outage that
causes delays in order fulfillment and delivery. The delays result in increased
overtime, usage of expensive couriers to ship products, and late delivery
penalties (predictive)
• Machines number XX, YY and ZZ can handle the production load in case the
failure happens. The best load distribution in case of ABC machine failure is
25% of its load to be handled xx, 50% by YY and 25% by ZZ (Prescriptive)
Good luck selling analytics … Ashraf Osman, Cairo 2017