NextStage & Web Analytics Vendors a Proposal for the Future
Exploring collaboration possibilities between NextStage Analytics and Web Analytics vendors.
NextStage has worked in the field of Web Analytics, however differently and complementary to what others such as Omniture, WebTrends, Coremetrics, Unica, etc…
NextStage OnSite (NSOS), the product we will be launching next year, is a tool giving you complimentary reports that Web Analytics tools don’t provide. Or as Dennis from Yahoo! likes to call it data points 
First: what does NextStage OnSite do and how?
On a technical level, we incorporate a unique JavaScript tag on your website, also called plain vanilla tag. The JavaScript is exactly the same on every page, you only have to make sure that it’s placed on every page you want us to track.
Once the code is inserted and if you have a valid account, our systems gather data, loads of it! Don’t worry, this is completely transparent and non intrusive for you and your visitors. What do we track? Mouse movements of your visitors and they keyboard strokes (not what they’re typing but when).
We provide reports and recommendations (regarding recommendations see my second PS at the bottom).
What reports does NextStage provide?
I already explained some in earlier posts as age and gender or the Tirekickers report. Let me give you a few more:
Failure pages
Web analysts often look at Exit pages: “From which pages are my visitors leaving the site?“.
If it’s your eCommerce thank you page, very good, but this is usually not the case. Exit pages are often not the issue and let me tell you why. If you’re on a website and you’re looking to buy something (or looking for support), you will start looking around, searching or navigating. After a few minutes (or seconds if you’re impatient) you’ll start getting frustrated because you can’t find it… But if you really want/need to find what you’re looking for you’ll continue searching. In the end you give up and you leave the website. Was your exit page the cause of your frustration?
No, your frustration came before, and current Web Analytics tools can’t know that as they measure clickstream data. NextStage analyzing how the visitor is thinking while browsing the site, can see when he’s getting frustrated and reports upon, what we call, failure pages.
Failure pages are the pages that create frustration to your visitors and by having this information, you’ll know where to put your optimization efforts. You might want to rethink those pages, do some A/B testing to see if you can improve them. I’ve been in the WA Industry long enough to know that most end users struggle in the action part of optimization and often it’s because they simply don’t know where to start. This report allows you to learn what you really need to optimize.
Here you have an example of this report from our prototype (notice the date?). In this example you see very clearly that 1 page is a huge failure page (red bar) and another one would benefit some revisiting (yellow bar). With this report you can easily decide where to test & optimize.
Interest level
This report will work in combination with another dimension that you define. You can report interest level by age or gender, allowing you to know which gender/age group is more interested by your website.
Retention/memorization
Which users are more likely to memorize the message transmitted by your website? If you’re for example a brand or you’re launching a new product, this is something important to you as a visitor retaining your brand/message will be more valuable to you than a visitor who will forget your message. You can view this in conjunction with other metrics such as age or gender.
Visitor expectations’ matching
This report provides you with a clear view on how well your website is performing against your visitors’ expectations. We report this in three categories: expectations matched, expectations unmatched or unsure. Why is this important? If you’re in sales you’ll learn that managing your prospect’s expectations is crucial. If you fail in addressing their expectations, you will under-perform as a sales person. A website is no different.
Visitor experience
This report tells you how visitors perceive the experience they are having with your website (and with you indirectly). It is not declarative such as surveys: it provides you with how they really think the experience was. We provide three categories: good experience (the visitor exited the website satisfied with the time he spent on your site), bad experience and indifferent.
Visitor success ratio
Your visitors have an objective in mind such as finding information about a product, getting support, buying something… This report allows you to know if your visitors were able to do what they wanted to do. 3 categories are once again reported upon: successful visit, unsuccessful visit and unsure.
These are some of the reports that will be available within NextStage OnSite. This is not about page views or number of visitors but about your visitors and how they think, therefore it’s about marketing and business objectives. Are you engaging with the right audience in the most appealing way?
What’s the opportunity for Web Analytics vendors?
Our aim is to allow web analysts to continue using a Web Analytics tool, adding our reports so they can segment their data in a new way. We don’t provide classical WA reports and we don’t want to go down that road as lots of smart companies are already doing that. Instead we’re looking for one or two Web Analytics vendors to work with in order to integrate our dimensions into their tool.
What can be done with NSOS + WA?
Imagine that you’re selling different products on your website and each have a different target. To keep this simple, let’s say that you sell products for men and different products for women. Thanks to NSOS integrated with your WA data you will be able to see if you ‘for men’ products are really appealing to men and vice-versa. I’ll let you come up with other applications using our reports combined with your current ones. Don’t hesitate to share them!
Why is this a good opportunity for the vendor(s) to partner with us?
Since the advent of free tools, paying tools are struggling with their unique differentiation. As additional functionalities are being rolled out by free tools, competition will increase. Nowadays, all conferences that I attend, the same question comes over and over again: Why paying for a tool if free tools like Y!WA and GA do what most paying tools do? Eric has started an interesting discussion about this topic. It’s time for paying tools to find competitive advantages and NextStage OnSite can help.
So if you’re a vendor and want to learn more, don’t hesitate to contact me or if you’re be attending eMetrics Washington this year, come and speak with me.
Cheers,
René
P.S. Keep visiting, there’s more to come.
P.S.S. NSOS will also include recomendations, I’ll explain this in a future post
Bonjour René,
si je comprends bien, la distinction de sexe ou d’une catégorie d’âge repose toujours sur un questionnaire – même si les questions ne sont pas “directes” ?
En quoi le mouvement de la souris est-il pertinent dans ce cas ?
merci pour ta réponse
Bonjour Denis,
Merci de ton commentaire, je réponds en anglais pour que tout le monde comprenne.
Denis from DigitalCommunication.fr (France) is asking the following: if I understand right, the gender distinction and age category is done thanks to a questionnaire- even if the questions aren’t ‘direct’? What’s the purpose then of the mouse movement in this case?
Maybe my explanation didn’t come through, let me explain but first, to allow our readers understand the context, I believe that it comes from the ‘Predicting Age and Gender White Paper that I published last month‘. Please go through it to fully understand the question.
The test we did was with a Market Research firm and they have panels of people to which they ask questions from time to time online or by phone. During the test, the purpose was to have 300 people going through some pages allowing our technology to gather mouse movements and keyboard stokes. NextStage didn’t use the results of the questions that were addressed to predict age and gender. We only used mouse movements and keyboard information (when they type not what they type). Thus the prediction was done solely using that information and not the answers to the questionnaire.
The technology works on websites in which people don’t answer any question and we’re able to predict Age, Gender and many other things just by looking at how people move their mouse and type in their keyboard.
I hope this clarifies you question. Don’t hesitate to comment again if something is still unclear.
Amicalement,
René