CRM and Big Data

When we say CRM, people immediately think of customer services and support, a random executive making calls, earning brownie points with the customers, selling them sweet deals or loyalty discounts. Sure, CRM involves all of this but there is more to it. Customer relationship Management is not just about good servicing and great support. CRM is about customer experience and customer delight right from the intermediate stages of the conversion funnel. CRM in fact includes marketing, synchronizing sales, customer service, support and even predictive and behavioral analysis.

This means that as soon as you reach out to your prospective client you have to start building an experience. It also means that once you have acquired a customer, you have to work on understanding him and winning customer loyalty. Especially in the Apps industry where customer attention spans are short and uninstallation rates are high.

Data is the key, but have you ever wondered what metrics do you need to measure and how can this data be used to build the haloed experience that everyone is talking about? The answer lies in analytics. Bringing together huge amounts of data and establishing correlations for better application is the very heart of Big Data Analytics. For insights into how you can pool Big Data and CRM to drive in better revenues read on:

Segmenting Your Valuable Users:

Let’s say you have just completed the first round of installations.Prior to which you have had no interaction or insights barring the intelligent guess work and some vanity metrics from tracking installs. The next step is to track in- app behaviour but what after you  have data points on your customers? Using metrics to separate grain from chaff is the next challenge at hand.

Let’s take the example of eCommerce applications. In a 2013 Accenture study 41% Millennials admitted to window shopping on eCommerce apps. That means 41% of the majority that spends on shopping online is a part of the fauxsumerism brigade. You can not trust the cyber footfalls on your app to measure performance or to target the right customers. Then how do you market to the right consumers?

You build segments with the right events. With advanced segment builder features in analytics tools such as mTraction, pooling valuable metrics and building segments with data points is an easy click to build activity. In the case of an eCommerce app, rather than measuring the wishlists or MAUs (Monthly Active Users) measure cart values and check outs.  Market luxury products to the segment with higher cart values,  they are most likely to buy them. For the segment that doesn’t buy, try sending discount coupons that tempt them to  complete check outs. This is how you best use Big Data & CRM features for marketing and sale conversions.

Push The Right Buttons:

After the segments are built, sending out interactive push notifications is the next step. Push notifications too need some solid homework. Data on pushes and how they perform is necessary to chart out the next Push campaign. Also simulating Pushes for better  performance and User Interaction is a necessary step. Keeping a tab on pushes and launching campaigns at the right time, targeting the right customers can be achieved with a CRM tool that has all these features.

Predictive Analytics for Augmenting User Experience:

We just witnessed the Black Friday and the Cyber Monday, buying trends that are now known by dedicated names and days . How did we come to the conclusion that online stores need to be sell outs to sell more in December?
It’s years of Big Data pooled together and the common sense that the festive season calls for shopping mania. This is a macro scale example of how one can predict events and hence optimize for better sales or engagement. Similarly there are events on a smaller scale, on a day to day basis. For example, a statistical report suggests that for gaming apps ( July 2104- February 2015):

62%users install on buying new phones ie new device ids.
Most avid gamers in USA, spend 9 hours weekly on mobile game apps.
Roll play and strategy games can monetize really well.

How can you use this data as a gaming app owner?

You just decoded three key features about gaming apps, the most likely installers, the most profitable geography, the most cashable freemium models and how they may fair in the future based on the pattern. This may not be the direct interpretation of the available numbers but they help in predicting likely behaviour. They can help you make early decisions such as :

1. Find ‘new device’ IDs, segment them, market aggressively to them.

Upscale the freemium models with new roll play features in push notifications.
3. Market more to avid gamers for gaming apps by segmenting them in specific geographies.

This is analysis of previous data to extrapolate expected user behaviour.  Analytics is different from statistics, it doesn’t only read data it employs it for future/likely implementations. Your CRM tool should help you analyze and not just read data and help steer strategy in the direction of expected user behaviour.

Customer Delight with CRM:

There’s a one thing called customer satisfaction, which is the bare minimum one has to do to outlast competition. But to truly beat competition customer delight is the key word.

How can mobile apps delight customers?

The difference is between giving the users what they ask for and knowing what the user wants.
For example: The user profile and statistical data is visually represented as:
Female, 25 years, Active between 4 to 6 pm, weekly activity -> looking for flight tickets to Kuala Lumpur.

It would be fine to show the booking segment as the user opens the app. It would be an absolute delight to the user if at 3:45 pm the user receives a push notification saying that your app offers 10% cashback on flights to Kuala Lumpur for the users who buy in the next two hours. See the difference?  The user is almost sure that they’ll buy from you because while other apps are busy hiking prices, you just offered a valuable discount. You have won a conversion and perhaps a loyal customer. That’s the power of data, that’s how you can use it to build a strong relationship with your customer.

Applying Big data to establish patterns, predict deviations is a task cut out for experts. Data Scientists and Analysts grapple with not only making these interpretations but communicating them as logical, comprehensible insights. Reporting this data is a critical step and demands readable and comprehensible reporting.

Thus to maximize gains your CRM tool should be able to:
1.  Employ data in easy to use features that help you in insightful application of the same.
2. Make comprehensible reporting systems that give you quick insights for better action plans.
3. Provide quick  means to interact with customers.

Try mTraction for easy to build segments, interactive and intelligent pushes and easy to interpret reports. Make smart decisions powered by smart analytics.

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