Analytics Insider

As promised, here’s part two of the exclusive Q&A with WebTrends’ Tim Kopp about the company’s latest product, Score.

How does that translate into actionable strategies? Can you offer our readers and example of how to take that data and use it to boost conversions, for instance?

With WebTrends Score adding depth to your online visitor profiles now you are able to provide focused, targeted marketing messages. In our travel example, now you can target those visitors who are most engaged and most likely to convert with a very specific message about all inclusive travel packages to the Caribbean.

Score gives you the ability to find out who is most engaged prior to a conversion event so you are able to focus your efforts on only those visitors with the potential to add value to your business. Not only does this lead to increased conversion but also greater efficiency in your marketing effort because you are having conversations with the right visitors.

As markets continue to fragment, higher demands are placed on the timeliness and relevance of a message. WebTrends Visitor Intelligence helps marketing analysts quickly uncover, target, and act on micro-segment opportunities. Unlike web analytics vendors limited to broad, single-visit segmentation, WebTrends Visitor Intelligence enables ad hoc, multi-dimensional analysis of data centered on individual visitor profiles that become richer over multiple site visits.

How else can this new suite of tools help web site owners optimize?

With WebTrends Dynamic Search, an on-demand solution that captures real-time data from major search networks, analyzes performance, automatically adjusts the variables, and re-allocates online spending to profitably scale investments. The industry’s most sophisticated search marketing solution that leverages True Optimization to continuously monitor, measure, and tune the variables impacting the success of paid search advertising.

WebTrends Analytics provides comprehensive optimization into all aspects of the online experience, driving increased customer engagement, response and conversion.

• Comprehensive insight to optimize all aspects of the online experience, from marketing and organizational productivity, to site content and usability, driving increased engagement, response and conversion.

• Powerful collaboration tools and KPI dashboards deliver insight across organizations to understand and improve how visitors interact with web sites and marketing initiatives.

With web analytics getting more mainstream recognition and companies looking to undertrained employees to report on analytics, I’ve seen several disturbing trends. Hence, I’m going to start a series on Bad Analytics Trends.

The first of these trends in the idea that correlation does not equal causation. If that sounds like Greek to you, let’s define what we’re talking about here.

cau·sa·tion

the action of causing or producing.
the relation of cause to effect; causality.
anything that produces an effect; cause.
cor·re·la·tion

mutual relation of two or more things, parts, etc.
Statistics: the degree to which two or more attributes or measurements on the same group of elements show a tendency to vary together.
The idea here is that just because two metrics seem to go up and down together, doesn’t mean that those metrics are directly affecting each other. Let me give a practical example.

You are running a lead generation site for a service business. In looking through the data you find that users who visit your testimonials page are 50% more likely to submit a Request for Proposal. From this you could deduce that

Your testimonials page makes people more likely to convert
Testimonials alone make people more likely to convert
None of the above
While it’s tempting to believe points 1 or 2, you really shouldn’t. Maybe they are true, maybe they aren’t. Here’s why. Based on the single data point, there’s no way to tell whether seeing the testimonials page caused people to submit the RFP or whether people who had already decided to submit an RFP are more likely to make a quick stop at the testimonials page during their visit.

The real problem is when companies start making decisions based on these incorrect assumptions. Decisions like, “Let’s put a big ‘Ol link to the testimonials page on every page!” or “Let’s put testimonials all over the site so people see them everywhere!” are not founded. They may end up helping (coincidentally), but don’t pretend they are genuine data-driven decisions.

Anyone have any examples from personal experience to share?

AnalyticsInsider talked with WebTrends’ Tim Kopp about its latest product – WebTrends Score. Listen in on part one of this interview.

How exactly does WebTrends Score improve the way marketers quantify visitor engagement and measure the value and interests of customers? How is it different from what’s out there today?

WebTrends Score provides measurable insight into visitor intent by allowing marketers to create custom scoring rules based on activities that visitors conduct on a website and apply multiple scores to a single visitor, visit, or campaign.

It gives you a rich multidimensional view your website visitors allowing you to measure the value of visitors to your site before they convert so you know where and how to spend your time and marketing budget more effectively to increase visitor conversion. This is differs from other solutions which apply a single score to a visitor or visit.

What types of rules do WebTrends Score users use to measure the level of engagement or interest visitors have in content? Can you offer some examples?

Different scoring rule sets can be applied to different content. As an example, maybe you are a travel website and sell cruises both to Alaska and to the Caribbean. You would have a rule set for each of those content categories. You will likely have visitors who score low on Alaska cruises and score very high on Caribbean cruises.

With Score you not only measure that they are more interested in taking trips to the Caribbean, but you measure the degree of their interest. To take the example a step further you may also want to create a rule for all inclusive packages. Now you can find visitors who you know are not interested in going to Alaska, but do want to go to the Caribbean. They are also interested in all inclusive packages.

Check back tomorrow for part two of this exclusive AnalyticsInsider Q&A.