Customer typology and metrics for the Web

In this post I give my point of view about the different types of customers that can be used by marketers, I also adress the problem of defining metrics to qualify these customers.

Customer Profile

A person with whom the company/website is in contact can be:

• A Potential Customer (Also called Prospect): This is, typically, a person who is the target for a publicity campaign and who has responded positively (i.e. who has actively looked for further information).

• A First-time Buyer:  He has just made a purchase unaware that things are about to snowball!

• A New Customer:  This customer has bought the product and is discovering its qualities as well as the company’s services. He should receive very good attention and treatment with the aim of gaining his loyalty (losing him at this stage would be very expensive since the cost of a first buy is very high and the chances of him returning at a later stage are low).

• The Unhappy Customer: There are two possibilities: either the client can be reassured about the company’s services (in this case consensus must be found), or else it is already too late (in which case he must be allowed to leave quickly and with as little fuss as possible).

• Reference Customer: This is a happy customer who is ready to speak in favour of the product/company to potential customers.

• Company Advocate: This user spontaneously finds customers for you (think about it…haven’t you ever recommended Google to your grandma?).

You have probably understood that the previous customer’s profile is linked to company loyalty.   Let’s now take a look at the parameters used to classify customers using the loyalty criterion, specifically for web use of course!

Measuring web loyalty

The simplest metrics are also the best known ones:

• Browsing frequency: How many times a month does your customer browse your website? A customer who browses often and buys enough and frequently is good, otherwise a hard look at both sales arguments and website is necessary.

• Browsing time: How long does your customer browse for?  (it is best to know minimum, maximum and average times here). Again, a customer who browses for a long time without subsequently buying is not a good thing.

• Purchases per visit, number of items per purchase, sum spent per purchase: These figures allow us to classify customers according to their potential to create company revenue.   This is important because a customer who browses ten times less frequently than others, but who spends 100 times more, must be given special attention and deference.

If possible, it is also useful to know:

• Number of referrals made:  How many people visit the website through direct referral by a specific customer?   This is one of the best indications of customer loyalty.

• Referral value: How much have the people who have been referred to the website spent?  This metric doesn’t measure the referring customer’s value but his persuasive power and his suitability to your (virtual) sales area.  If a customer refers many first-time buyers who then spend a lot, then spoil him!

• Taking part in Website life:  Does the customer answer questionnaires, play games and take part in customer fidelity programmes?

Lastly, if your website can identify these customers and personalise their navigational experiences on it, it is good to know the customer personalisation index (LinkedIn does this) in order to measure degree of involvement.  This index is equal to the number of personalised elements divided by the number of elements that can be made personal.

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