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What will a Chief Customer Intelligence Officer do?

In my last post I talked about the value of a Chief Customer Intelligence Officer.  You may be wondering, what would a Chief Customer Intelligence Officer do?  Here is a high level summary.

1.  Integrate insights across teams.  There is a wealth of customer intelligence being uncovered by your Big Data, CRM, Digital, Market Research, and Social analytics teams among others.  However, insights need to be shared so that the company benefits.  For example, I recently shared customer insights from the CRM group with the Social team to insure that the best current customers were targeted on Facebook for a promotion.

2.  Identify the story within the data. Customers are telling us how they feel about the brand and what their intentions are with every action, whether it be a call into the call center, a visit to your website, a comment on Facebook or a purchase in the store.  By triangulating all the available data, you can get a fuller picture of different customer segments and socialize their stories to senior management.  For example, I found that there were three types of visitors to a client’s website.  By layering on customer data, I was able to see which on-line attributes were most closely related to off-line purchases.

3.  Develop a customer strategy based on the data. Once you have identified customers’ stories, you can insure a consistent and compelling customer experience across channels.  This is the result of synthesizing the wealth of information and integrating analyses to support the strategy.  For example, web site activity could trigger a direct marketing piece for some customer segments.

4.  Manage a cross-functional team. To accomplish all this, the Chief Customer Intelligence Officer will need to manage a cross-functional team that encompasses Big Data, CRM, Digital, Market Research, Social and any other analytic teams within marketing. This will facilitate the integration of insights and development of a consistent customer experience.

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5 reasons why your next hire should be a Chief Customer Intelligence Officer

Have you heard the story of the blind men and the elephant?   In this famous Indian legend, a group of blind men touch an elephant.  However, each man feels just one part and it is a different part of the elephant for each man.  They compare notes on what they felt and are in complete disagreement.  In many ways, this is how the customer is seen by some companies.  The digital marketing team has one view of the customer, the product marketing managers have another view and creative might have a third view.  Here are five reasons why you should hire a Chief Customer Intelligence Officer who will integrate and disseminate insights for a holistic customer-centric approach:

1.  Grow revenue. An integrated understanding of your customers and their journey with your company will enable you to up-sell and cross-sell effectively to them. Only with a comprehensive view of the customer will you know whether he wants more of the same or if he needs something different. Rather than the product managers focusing on promoting their products and meeting their sales goals, customer preferences and needs would take precedence.

2.  Reduce acquisition costs. Consolidating insights across channels and products will enable you to segment your customers by purchase history, demographics, lifestyle, lifetime value, etc.  Thus, you can provide the right message to each segment and find new customers who look like these segments.  With better targeting and identification of your best customers, you can find new customers who are similiar.

3.  Enhance customer retention. Customers expect a coherent and consistent customer experience across channels.  If you integrate insights and provide an experience tailored to their needs, behavior, and attitudes, they are more likely to be retained and become advocates of your brand.

4.  Improve campaign performance. Customer insights from the direct marketing channel can inform strategies used in the digital marketing channels and vice versa. For example, you could re-target visitors to your website or social media advocates via direct marketing.

5.  Increase customer satisfaction. Customers will reward your focus on their needs and preferences with increased satisfaction and willingness to recommend your brand to others.

 

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Are your customer insights a source of competitive advantage?

My prior post talked about the value of customer data.  Your next question will naturally be, “so how do I leverage what I know about my customers to my advantage?”  There are many ways to transform insights into  increased market share.  The lists below are examples but by no means the only things you can do.  However, I would suggest that you see your customer data and its application as a source of intellectual property, something to be guarded and leveraged wisely.

It can enable you to increase revenue by:

  • Identifying those likely to buy in the near term
  • Separating those customers who need an offer to get them to buy versus those who would buy regardless
  • Determining the right accessories or ancillary purchases to promote based on a customer’s purchase
  • Highlighting the “next best” products based on your customers’ purchase patterns

It will also help you retain your customers by:

  • Understanding the customer journey and the experiences that matter
  • Identifying those likely to defect
  • Ranking your customers by their lifetime value so you can reward your best customers

Lastly, it can also help you reduce your costs by:

  • Enabling you to conquest smartly, targeting those that look like your best customers
  • Determining the best conquest sources and communications

Are you leveraging your customers’ data to increase your market share?

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What are your crown jewels?

A former colleague of mine always referred to his clients’ customer data as their crown jewels.  He had a point.  No one else knows as much about your customers’ behavior, attitudes, and preferences.  If your customer data doesn’t seem valuable to you, imagine if your competitors had access to the very same information.  What would they do with it?

There has been lots of talk about analytics as a source of competitive advantage.  More recently, big data has promised to uncover untapped value and insights.  However, have you thought more holistically about the resulting customer insights and intelligence?  Used wisely, what you know about your customers can be a source of competitive advantage.  It can help you increase market share by promoting the right product at the right time to the right person using the right channel.  It can provide insights that enable you to improve marketing ROI, conversion rates, and conquesting.  It can help you identify customers likely to defect,  uncover what you need to do to retain them and help you determine if they are worth retaining based on their future lifetime value.

Finally, if you aren’t thinking about your “crown jewels”, I bet one of your competitors are.  They may be able to purchase data about your customers from a third party vendor and use it for conquesting.  If you don’t think customer data is valuable, your competitors do and they are willing to pay for it.

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How do you prioritize new customers?

I was asked recently how to prioritize new customers if you do not have demographic or firmographic data available.  In other words, what can you do with just the data from the first purchase with which to work?

To make this more concrete, let’s consider the following situation.  You are asked to call each and every new customer who has made a purchase.  The question is, how do you prioritize the calls?  You want to make the first calls to those with the greatest potential to become loyal and valuable customers.  The only data available relates to the first purchase:  total revenue generated, products purchased,  product revenue, etc. 

In this case, a linear regression could be used to help you identify the factors that predict lifetime value.  (Other types of models can be used depending on the independent and dependent variables available.)  Using your existing customer base, build a model that leverages data about the first purchase to predict lifetime spending.  You can identify the best and worst new customers using the resulting model equation.  Armed with this insight, you can test your model by calling on new customers with the best predicted lifetime revenue and a random selection of new customers regardless of predicted lifetime revenue.  In addition, you can test call back timing to determine if there is an optimal call back window. 

Even with limited data, analysis can lead to insight.  Further, there is always an opportunity to incorporate testing.  In this case, testing can validate initial findings and help you learn more about the purchase cycle.