Customer Dimension’s changing Dimensionality

“Who exactly is my customer?”, a typical question that is asked by Sales and Marketing folks every day. This is a simple question, but an extremely tough one to answer. Sales cycle in any organization deals with two types of customer facing activity, which can be classified into either acquiring a new customer or increasing existing customer’s lifetime value.

BI provides a platform to understand and try to answer the question. Customer dimension is one of the toughest data dimensions to manage due to the enormity of unknown attributes. It will be surprising to note that master data collected from customer ends with simple contact information in several organizations. Types of analysis was restricted to buying analysis and were in lines of asking the question “What Happened?” Data mining techniques and analytics provided limited insight into existing customers, but were handicapped when trying to identify new customers. Image source business2community.comThis was primarily due to dependency on the limited data that was provided by a customer. A common problem when you try to understand a customer and after careful analysis of behavior patterns, encounter an “Ah-ha” moment, the entire profile shifts into new pattern. It is enigmatic to synthesize and construct an accurate picture of the customer with limited data.

Today organizations employing a variety of methods to to augment the in-house customer master data. Social media is proving to be a haystack, but a useful one to be explored in detail. Organizations have started asking details such as Facebook Profile or Twitter Handle as part of customer master data. This information gives insight into a customer’s likes, dislikes, wants, needs, aspirations etc.

Organizations use the data to first understand both existing as well as potential customers. Knowing the customer profile makes it easier to tailor products and offerings to different segments as well as measure the effectiveness of such activities in near real time. A great and unlikely example of this phenomenon is Milwaukee Brewers baseball team.

Another type of analysis typically performed is to monitor market sentiment. It is an instant feedback mechanism that sometimes even snowball into a Public Relations nightmare. Good example is the spike in Twitter activity seen during launch of iPhone and iWatch by Apple Inc (Read the full article here).

This shift in data collection is predominantly restricted to Consumer facing industries such as Retail, Sports, Hospitality, Restaurant, Apparel, Entertainment etc. Customer analytics is an evolving area with new technologies introduced almost on daily basis. Growing from social media trend, customer analytics is slowly making in roads into mobile devices today.

Customer dimension data can never be replaced per se. Social media only provides added value on top of existing data. Any analytical model can be  easily verified against actual fact data available.

NOTE: Traditional methods such as cold calling, referrals, road shows, conferences, television, radio, newspaper etc still do make an impact in sales.  These channels of reaching out to customers cannot be discounted.