Growth or revenue creation can be fueled by two mediums: selling to a new customer or selling to an existing customer. We’ve written about using data and analytics when prospecting and selling to new customers, but how does it translate when selling to existing customers?

Upselling to customers has traditionally had an unpalatable nuance to it. The sole objective has been to get the customer to buy more. I can’t help but think of that car salesman who’s aggressively overselling that 4-door executive saloon, packaged in full options, when your only need is to get from place a to b. Knowing your customer in and out is what separates a pleasant buying experience from an unpleasant one.

The combination of internal and external data in customer analysis opens up a whole new world when upselling, and is something that every company should seriously consider.

In a world that is more data-driven than ever before (according to IBM, 90% of all data has been created within the last two years alone), why not utilize some of this data when making that upsell? When you know more about your customer, not only does it make the buying experience more enjoyable to the customer, it also creates value to the organization. The most notable benefits are:

  1. It builds a deeper relationship of trust and commitment
  2. It’s cheaper (and sometimes easier)
  3. It increases the monetary value of a customer

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Some industries have taken a big leap forward when upselling by means of customer analysis; most notably eCommerce retailers, banks and insurance companies. These analyses are mostly based on internal data that the company has gathered over time. For example, segmenting customers based on demographics, location, profitability, size etc. can give a good indication of products or services the customer might need next. Previous purchasing behavior can also signal future buying intentions, which is well known in the world of eCommerce. But collecting internal data requires a lot of time and effort. However, external data rarely ends up being a part of these analyses.

The majority of companies aren't combining internal behavioral data with external open and public data, even though it opens up the door to more intelligent discussion and a higher level of customer service.

The whole concept revolves around combining internal (behavioral data) and external data (changes potentially impacting future behavior). Including external data in customer analysis is something that a majority of companies are not yet realizing to the fullest potential. So how does one spot upsell opportunities in the existing client base? Just as in new business sales, timing is everything and conversations should concentrate on immediate need. The whole selling process starts by identifying an opportunity or concentrating on a particular need, and can stem from internal or external signals.

Following Customer Signals

Even "less significant" signals such as recruitment ads posted by a customer, can signal future needs - anywhere from needing new office space to upgrading their CRM solution. Slow response to external signals can also act as a gateway to losing a customer, for example in the case of a merger or an acquisition. Your competitor might react to this and steal the customer in the midst of the organizational change.

Time and time over companies say, “we know our customers very well” or “we’re in contact with our customers on a monthly basis, so we know what’s going on”. The truth of the matter is that they really don’t. From the customer's viewpoint, this will be viewed as product or service pushing aka “chasing the dollar”. Why shy away from using data when it can provide a more intelligent discussion and provide a higher service level to the customer? The combination of internal and external data in customer analysis opens up a whole new world when upselling, and is something that every company should seriously consider.

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Topics: Data Open Data Big Data

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