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SAP CONSUMER INSIGHT 365

Making Sense of Big Data, every day

Ultimately, we developed an intuitive and user-friendly tool that allows marketing analysts to customize the data they view through a modular set of insight panels, shifting the focus from time intensive data cleaning to seamlessly discovery of key customer insights. The speed and power is courtesy of SAP HANA. Intuitive customer trigger points allow analysts to enter a location and time and immediately see a range of implications they never had access to before, facilitating quick, accurate decision-making and forward planning.  

 

To protect the privacy of individual mobile subscribers, data is anonymized before it reaches the analysts. Identifying data never leaves the mobile operators’ systems, putting an emphasis on trends across cohorts rather than the patterns of individuals. While analysts have previously needed to make assumptions based on data from small sample sets (for example, 5,000 subscribers out of a few million), they can now make informed decisions based on real subscriber data. Operating at the intersection of mobile usage, big data, and cloud computing, SAP Consumer Insight 365 delivers a powerful data analysis tool enabled by elegant designs.

Prototype: http://31sw45.axshare.com/home.html

Product overview on SAP.com: http://go.sap.com/product/crm/mobile-data-analytics.html

Introduction slides: https://www.dropbox.com/s/7lqdru3akjccafr/SAP%20Consumer%20Insight%20365.pdf?dl=0

Marketing video: http://www.youtube.com/watch?v=A6EXOxNmoCE

 

 

PROJECT BRIEF

SAP Consumer Insight 365 is a new cloud-based analytic platform powered by SAP HANA. By gathering millions of anonymous data points every day from mobile operators and organizing the information in a meaningful way, marketing professionals can now efficiently discover rich consumer insights and make informed business decisions.

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Examples of business decisions:

  • Determine the optimal time and place to advertise

  • Discover what potential customers are searching for in a particular geographic area

  • Learn what the next hot trend will be

  • Decide on the best location to open a new store

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The conventional way of sharing insights with clients boils down to analysts presenting datasheets, slide decks or printouts. It is an inefficient and time-consuming process to communicate with clients, who end up with inflexible, information poor deliverables they cannot manipulate.

APPROACH

Applying design thinking methodologies, we began by conducting design research interviews with 20+ marketing analysts from 10 different companies with in-depth understandings of the media buying space. From these interviews, we were able to identify that while analysts had a diverse set of use cases for presenting data, they had similar analytical needs. Analysts needed the ability to slice and dice the data and capture snapshots to identify patterns over long periods of time. Because the ways in which they presented data varied, we needed to design a solution that allowed the user to present their analysis in a modular way, thus accommodating the range of customers they work with.

 

After synthesizing these findings, we were able to come up with design ideas that fulfilled the critical needs they expressed, focusing on minimal preparation time for data cleaning prior to analysis and the need for a customizable tool that could be tailored to diverse use cases. End users reviewed these initial concepts while an SAP development team evaluated the technical feasibility of the solution.

SOLUTION

REFERENCES

Key Features

  • Customizable controls and filters

  • Intuitive drag and drop interaction

  • Accurate, clean, and searchable datasets

  • Meaningful and consumable data visualization

  • Interactive report sharing with customers

CHALLENGE

Finding the needles in the haystack

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Old tools lead to high training costs

Analysts spend more than 50% of their time creating data visualization reports for their clients using outdated tools instead of getting insights from the data. What’s more, companies spend significant resources training analysts how to use these tools.

Static deliverables

Sifting through and making sense of big data is the biggest challenge marketing analysts face today. The insights are there, but too much time is spent trying to find them.

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