AnalyticsAnalyzing Customer DataMore on Buying Processes and Data Analysis

More on Buying Processes and Data Analysis

The raw data coming off any sizable Web site is so copious, so unmanageable, that analysis paralysis is sure to set in unless you first take the time to determine which measures, and which data, actually matter to your intended results.

In last week’s article, I looked at a good model for evaluating your customers’ relationships both with your product or service and with the purchase process itself. Many other models are also worth noting. My hope is that by looking at a range of options, you’ll find one that works for your business. And if you don’t, you’ll be able to use the models as a starting point for developing a framework that fits your needs.

Some of you have asked why a column on collecting, analyzing, and using online data should be veering off in the apparently odd direction of sales cycles and customer buying behavior. Both my own experience with marketers and my conversations with many of the firms offering online data-analysis solutions have shown me that trying to make the Web measurable without first understanding which measurements are most important adds enormously to the frustration, cost, and time commitment of achieving a satisfactory data-analysis solution.

The raw data coming off any sizable Web site is so copious, so unmanageable, that analysis paralysis is sure to set in unless you first take the time to determine which measures, and which data, actually matter to your intended results.

Awareness of need, awareness of solutions, fact finding, persuasion, transaction, postsale information, and support: Those are many of the steps a buyer (consumer or business) goes through when making a purchase decision. The importance of any one step varies depending on the product, service, category, distribution arrangement, and lots of intangibles like market conditions and brand perception.

Are you introducing a whole new category of product, never before offered? You may need to focus the bulk of your marketing effort on creating a need. The right metrics here will reflect your success at making buyers aware that they have a problem — and one you can solve (but that part is secondary, because no one will care until they are convinced the need exists).

If you are selling a lower-cost “me too” entry in a crowded commodity-like market, the early steps may be safely assumed to be covered; your marketing effort has to focus on the information-gathering and persuasion stages. If that product is a high-end offering sold by a direct sales force, marketing may be best deployed in providing information, letting the persuasion happen face to face. If you sell through multitier distribution, perhaps you can’t rely on your channel to effectively persuade, and your marketing goals have to expand to include that piece.

Either way, you won’t be interested in online advertising data that deals in clicks or traffic; your focus will be on whether competitive, actionable buying information is being disseminated by your Web site, and whether that information is effective enough to send buyers out to the channel to complete the transaction. A radically different set of data-analysis requirements, eh?

Any of you have interesting examples from your own experience? I’d love to share specifics of how understanding sales challenges has helped a business determine what is worth tracking.

Write in with your success stories and your frustrations, and I’ll tackle them in this space. If you wish to be identified, include a line granting me permission to do so; otherwise, we’ll keep you and your firm anonymous.

Send your thoughts to info@ryanwhiteman.com. Thanks!

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