interview with jonathan levitt, vp marketing of iperceptions
This week, I am very happy to welcome Jonathan Levitt, Vice President Marketing of iPerceptions, one of the very top applications in attitudinal analysis, often referred to as Voice of Customer analysis. Since iPerceptions and ForSee Results are generally seen as the leaders of the field, and since I interviewed Larry Freed, CEO of ForeSee, last week, I thought I would ask Jonathan the same questions, and see how iPerceptions the behavioral/attitudinal mix can bring more added value than each of them taken separately.
JW – Could you tell us about how online attitudinal analysis has evolved in the last 2, 3 years, and where it is now (adoption, evolution, etc.)?
I think online attitudinal analysis went mainstream in the past year or so. We’ve all seen the hallmarks of its maturation: widespread penetration in all verticals, integration with behavioral research, firms specializing in specific sub-disciplines like open-ended quantification.
Basically, at some point everybody recognized the limitations inherent to clickstream web analytics and by now most of the big players have augmented their research toolbox with some kind of VOC solution. Having said that, I think the honeymoon period for attitudinal analysis may be drawing to an end. In 2007 and 2008, it was enough to have a VOC program ongoing without worrying too much about ROI; listening to real visitors was basically seen as an end in itself.
Now, with the scary economic situation, the game has changed. There is pressure on attitudinal analysis vendors to justify their worth, to prove their technology’s contribution to corporate bottom lines. As a practitioner, simply collecting and reporting out bland dashboard metrics–things like customer satisfaction scores, net promoter scores–and then patting yourself on the back isn’t going to be enough anymore. We’ve seen how this painfully deep consumer recession and the Wall Street crisis have wrecked companies like AIG, Wachovia, Bank of America, and CitiGroup–firms that had rock-solid customer satisfaction scores for years. So, metrics alone–even if they are directly sourced from real visitors–won’t save you.
Instead, I think the focus is shifting towards visit success and task completion. Companies want to know what tasks their visitors are seeking to accomplish, how they’re doing in helping them complete these tasks, and, most importantly, what they need to fix to boost visit success. When I talk to C-Level decision makers, I keep hearing the same thing: provide me with that one golden insight that will help squeeze more revenue from my site or help me stall the churn bleeding. Online attitudinal analysis is still better positioned that clickstream analysis to deliver this, but it requires vendors to think like business owners instead of ritualistically reciting dry and impersonal metrics.
JW - We are interested in data integration, can you tell us how iPerceptions can make its data available? Any API, or export schema?
Without infuriating our development team too much, I can promise you that APIs for both our enterprise-class and free 4Q services are most definitely on their way. I think this will be far and away the most seamless way to blend and mash-up iPerceptions data with data from other sources. Right now, we’re relying on a series of ad hoc measures–much as other vendors are. We’re using parameter-passing, FTP and direct downloads, and online file exports to do the job, but the flexibility of an API cannot be matched and we’re very eager to roll that out.
JW - We would like to know if it’s possible to integrate iPerceptions data with applications such as WebTrends or Omniture.
It certainly is. We have bilateral relationships in place with all the major web analytics vendors, making it very easy for an iPerceptions client to mesh together data sets based on a unique identification variable.
JW - Is it possible to somehow link respondents to what they actually did on the site? If yes, how do you technically accomplish that?
This is the first question that companies put to us. It’s important to note that a lot of interactive marketers and web analysts don’t have backgrounds in offline marketing research, where surveys have been going on since time immemorial. As such, some of them get a little bit nervous about whether or not their respondents are being fully truthful; they want some way to calibrate this with actual activity on the website. We’re more than accommodating and it’s actually a very easy process. If we’re dealing with a client who’s plugged into a BI platform like Omniture’s Genesis, then it’s really just a matter of setting up certain routines and then the machine basically runs itself.
JW - Without naming the client, could you give us an example of a company that actually linked their behavioral and attitudinal data? What was the most interesting finding that could not have been possible with only doing the survey?
I think most of the success stories in these types of situations all follow a similar tack. Company A has a particular series of behavioral segments that they want to analyze and contrast. Say they want to measure offline purchasing likelihood for visitors linking from paid search vs. display ads. So, essentially, they will graft survey data onto pre-established behavioral segments. They’ll do this until they’ve answered a question, and then the integrative research will reach a terminal point.
Most success stories tend to feature some variation on this schema. Our most exciting success story, however, came from a client that flipped this model on its head and did things the other way around. They took all the visitors would had indicated (through surveys) that they had successfully completed their primary tasks and those who didn’t and they grouped them into two distinct segments. They then built a composite sketch of these segments: age, gender, intent, top referrers, click paths, recency, frequency, etc. In the end, they discovered that the segment representing visitors who DIDN’T complete their tasks contained a huge proportion of several key target demographics. Conversely, their site was working at peak efficiency among visitors for whom they weren’t even optimizing. It was a massive culture shock for that company, but it smashed some unhealthy tenets that had been dearly cherished there.
JW - How do you see a solution like yours evolve in the near future in terms of better integrating its data with other enterprise customer data systems?
We’re always working to iterate, to improve, and to innovate in this area. Ultimately, I think the future will bring a broader reach for integration. We’ll go beyond marrying behavioral and attitudinal silos. The reach of integration will expand to include CRM, POS, and ERP systems (and many, many more acronyms!), as well social data coming from new standards like Facebook Connect. And then, we’ll all have to figure out a way to grapple with integrating the ocean of data coming from ubiquitous mobile web access. We are definitely entering an interesting and challenging era for integration.
JW – Thank you very much Jonathan!
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Jacques Warren on February 24th 2009 in Web Analytics, WA Applications