6 Challenges Operators Face in Monetizing #BigData

Kevin Outcalt, VP, Mobile Analytics and Consumer Insight, SAP Mobile Services

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1. Where is the data?

Data is stored in numerous silos across the

operator’s infrastructure – #CRM data in one

location, call records in another, billing

somewhere else, and so on.

It isn’t uncommon to find data locked in 16 or

more databases within a single mobile

operator!

#1

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2. So much data!

Compared to a year or two ago, operators are

dealing with 10 times the amount of data on

mobile-user activity, and that’s continuing to

increase.

#2

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3. Analyzing the data

To make sense of the raw data coming in at a

steady clip, operators need to analyze it. The

process could be as simple as auto-correcting

for age and gender, since many customers have

family, corporate, or prepaid plans.

#Demographic info combined with a user’s

usage history–through the use of predictive

analytics – can give operator a good idea of

likely areas of interest, such as if user might be

receptive to offerings based on fashion, sports,

or cars.

#3

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4. Analysing the data on the “fly”

Operators need to be able to conduct data

analytics quickly so that clients asking for data

insights don’t have to wait days or weeks for a

report to be generated.

If clients have to wait, then the info may not be

as valuable or relevant as it might have been

when the data was first requested.

#4

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5. Sales expertise

Operators realize that while their sales divisions

may have the expertise to sell mobile

communications services, they don’t

necessarily have the skillset or connections to

sell business or marketing services.

Having sufficient breadth and depth of sales

coverage will be critical to monetizing big data.

#5

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6. Data protection and #privacy

This issue is of the utmost importance when it

comes to big data. Mobile operators must figure

out how to monetize their data in such a way

that they are complying with privacy

regulations and safeguarding their customers’

information.

#6

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