(Not) understanding the customer journey

Think about the last time you bought a more important item online. Did you – as many online marketers wishfully summarize from inconclusive data – search for the product category and directly buy the product from a PPC ad? Or did you spend hours and hours reading reviews, asking for advice from friends, visiting vendor websites, watching YouTube videos and so on? If you are anything like the average consumer, it is probably the latter. And still, many marketers only look at the last ad someone consumed before buying a product, to judge performance.

When it comes to impulse products, things get a lot simpler. You get seduced by a good ad and you buy the product. Or you see a funny commercial which gets your attention, and you buy it next time you are in the supermarket because you vaguely remember it. But that’s not the process for more involved purchases. That’s why it is so important to understand that all the information you get from marketers that are selling less ‘important’ items does not apply a lot to the more involved product categories.

The truth is that there is not just one customer journey for the more involved products, almost every journey is different. Now, there are Attribution Systems which vendors sell exactly to solve this issue. With these you will be able to assign proper value to most of the ‘touch points’ along the way, but it still wouldn’t tell you about the review this person read or the ad they saw a year ago that they vaguely remembered. In addition, there are usually too few sales to be able to say anything with statistical significance about a specific ad, thus making these systems useful only to adjust budgets on the macro level.

So with all the information we have since the advent of the internet, the best we can usually do is take signals from various sources and optimize advertising towards those. For the macro decisions about what budgets to spend for which channels marketers should use input from research and surveys, data from CRM systems, attribution systems and common sense. For smaller decisions, for instance which PPC ad is working or not, the best signals are immediate, high intent and plentiful ones.

Immediate signals are actions that someone in your target audience can and will undertake as soon as they see an ad. So for instance, when it comes to a banner, clicking on it and signing up for a trial of your service. The signal also needs to be high intent. That means whatever immediate action you ask people to take, this action needs to signal a clear interest in your product. So instead of giving away free ice cream to get newsletter signups for a piano company, you give away free sheet music. Lastly, the signal needs to be plentiful enough so you can make statistically significant conclusions. Something which will give you hundreds of actions per ad in a reasonable period of time instead of the few high ticket purchases you get.

When you measure and optimize towards these kinds of micro signals, you are actually optimizing towards the right type of Attention. If your target audience likes your product, with attention comes consideration at the right time, and with consideration eventually come purchases.

There are of course lots of other considerations, but the message I would like to bring across is that for the more involved purchase decisions, you cannot always fully understand the journey, and you are probably better off trying to get the right kind of attention from your target audience.


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