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How ICRM can aid in decision support for enhancing customer relationships

by Vamsi Krishna Paramjyothi

The market today is mature and highly competitive with several players, providing similar services at competitive prices with new products being released into the market in short intervals.  Competition and the demanding customer, who is willing to shift to another product or service provider, unless his /her wants aren’t met readily, are giving companies a tough time.

With multiple players offering similar products/services, most customers are tied to one or the other player. In addition to that, competitors are vying for your customer, as a result customer retention has become critical for survival. Which means one should be totally aware of customer preferences; the value customers see in your product/services, customer preferred communication channels, etc. Understanding the customer pulse, launching innovative products and retaining customers is mandatory for survival in this industry. In such a scenario companies are relying on CRM to achieve the above mentioned objectives, then why are we seeing so many product failures or why are we seeing minimal response for email campaigns, etc. The industry benchmark for click rate of email campaigns’ is around 10% to 40%, based on the relevance of email content with client’s expectation.
 
Which raises questions like, can CRM really help to achieve the above mentioned objectives?  If yes then how? What is going wrong?
 
Analyzing the CRM projects implemented will show that CRM implementation was done to achieve operational CRM efficiencies. If CRM has to support in decision support and help in enhancing customer relationship by giving appropriate insights about customer then one has to implement “Intelligence CRM“ i.e. ICRM. ICRM is a framework to derive intelligence and insights to address specific business challenges by applying configurable decision support models on customer related data from multiple data sources spanning across the enterprise and beyond. This information required for decision support can be obtained only if operational data is translated into valuable information. Hence implementation objectives should move towards ICRM from Operational CRM (OCRM). With so much customer data readily available with companies, it is not difficult to derive these preferences by using proper modeling tools and Intelligence tools.

Reading all this you may wonder if ICRM is Analytical CRM which has been repackaged Smile However it differs from ACRM and I will touch upon these differences in my next post.

About the Author

Vamsi is a Consultant with Enterprise Solutions and has extensive experience in process consulting, package evaluation and implementation for Telecom and FMCG clients. He is managing a CRM project for a leading telecom company and has more than 5 years of experience in sales and marketing, churn management and customer experience management. Vamsi will blog on ICRM, PRM, marketing and churn management.

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Comments

My opinion of analytical CRM (refer SAS and ePiphany) is not confined to CRM data only. I have known couple of telecom providers where the analytical CRM applications take the feed from enterprise OLAP data base consisting not only CRM. Not only this, the statistical analysis is done in SAS as mentioned by the author. So what is lacking is how intelligently these analytical capabilities are utilised for proper business improvement?

To summarise I would prefer to say intelligent usage of analytical CRM is a challenge rather division (intelligence CRM vs analytical CRM) explained by the author based on CRM data vs enterprise OLAP data and usage of SAS/RTD tools.

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