We all know the power of understanding our visitors’ behaviors online — using Web analytics to understand clicks, movements, patterns, conversions, segments, and more. We have found ways to identify opportunities to improve site performance based on this behavioral data, which is great.
And many organizations are looking at attitudinal data using surveys to help understand how the site impacts their audience. Too often, though, there are three problems with this:
- Analysis is too infrequent.
- The survey is based on a generic site visit rather than on specific behaviors or visits to different site sections.
- It’s done in a silo, completely separate from behavioral analysis.
I was reminded of the power of understanding your clients’ attitudes the other day while on Facebook. That includes the power of positive or negative experiences in online communities, word of mouth, and the ease with which consumers can share information.
A friend of mine and founder of BazaarVoice, Sam Decker, had his Facebook status set to “Just got burned on a proposal by [company name here]. Avoid!” when I logged on one day recently. Clearly Decker didn’t have a good experience with this company and he was sharing that with all his Facebook friends. I figure everyone he talks to over a few days isn’t likely to hear good things about this company.
Let’s take a few steps back to examine a prospect’s negative experience. Let’s assume this started with a visit to the vendor’s Web site. A prospect spends time to research a few Web sites she may be interested in doing business with. She then decides she’s interested in starting a dialogue with one or two companies, fills out the contact form, and waits for that call or e-mail.
From a Web analytics standpoint, those are successful conversions and look great. Unfortunately, far too often the company won’t get back to this person fast enough and will miss out on striking when the iron is hot (a topic for another time). In other cases, the company will follow up and form a successful business relationship. But that doesn’t mean everyone leaves that process satisfied. And a negative experience like Decker’s will greatly impact future conversion from a lead to a customer.
It’s important to constantly check with your customers and prospects on how you’re doing. Whether this is online or off-, you can learn a lot about what works and what doesn’t. To expand on the three common problem areas mentioned earlier:
- Analysis is too infrequent. While Web analytics data is typically examined on a weekly or monthly basis, too often attitudinal data isn’t looked at on a regular or frequent basis. It’s analyzed when digging into certain issues at certain times rather than looking at things on an ongoing basis. Doing the latter can help you analyze trends and spot problems as soon as they start. ForeSee and iPerceptions do a great job of setting up these recurring analyses based on satisfaction and can provide a ton of good insight into your audiences’ attitudes.
- The survey is based on a generic site visit rather than on specific behaviors or visits to different site sections. While it’s important to understand your overall visitors’ attitudes and satisfaction level, tying attitudinal measurement to specific site behaviors can be very powerful. For example, what are the people who successfully check out from your site saying versus the people who start down the checkout process and don’t complete? Why are people leaving the site after they access the site view on one page? Take the time to understand the macro and micro view of your attitudinal measurements.
- It’s done in a silo, completely separate from behavioral analysis. So many companies miss the boat on this one. It’s extremely common for analyses of behavioral and attitudinal data to be completely separate, and they rarely feed into each other. This is a huge mistake, as often attitudinal information can help improve the analysis and insight generated from behavioral data and vice versa. If you have two different leads in your company responsible for these data types, lock them in a room and don’t let them come out until they understand what each other’s data can provide and have a plan for how they will use the combined insight together going forward. Only thing worse than a silo like this (completely wasted insight) is a company only looking at either behavioral or attitudinal data only.
We all understand the power the average site visitor has when she comes to our sites and when she starts a dialogue with us. Take the time to understand what works well, and identify areas of improvement. Focusing online is a great place to start understanding this, but you must understand it all the way through your online customer lifecycle. You don’t want to be the “company name” in a single posting, multiple postings, or discussions among friends.
Jason is off this week. Today’s column ran earlier on ClickZ.
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