by Paula Thornton
July 31, 2009 at 4:25 pm
· Filed under 2.0 Design Thinking, Analytics, Innovation, Intent, Interaction, Social Media, Web 2.0
Two differentiating attributes of 2.0 are adaptation and emergence. Adaptive systems rely on feedback loops for continuous assessment. Emergence is the result of self-organizing adaptation. The more fluid a solution architecture, the more readily it can adapt. But fluid architectures are not yet the norm and there will always be situations where more structure is needed. In both cases, we will still rely on individuals to call out a need for adaptation, effectively — change.
Collaborative Web 2.0 environments like getsatisfaction.com, while self-organizing — allowing people to solve problems among themselves — do not adapt. There is no real problem solving going on. People are either sharing information for things that aren’t really problems (lack of knowledge) or they’re devising workarounds. Until the workarounds are acknowledged, there will be no changes to really ‘fix’ the problem.
Consider the volume of money spent on marketing, sales and even customer service — all focused on gaining customers and business transactions. What ratio is that compared to money spent to ‘allow’ individuals to interact with a business, clearing the rubbish that gets in the way of people who ’show up’ to do business? I’d like to call this the intent ratio: how intent businesses are at addressing the intent of their consumers. Companies might focus on measuring ‘retention’, but are inattentive to the business ‘machine’ and its health, starting with the points of interaction — the touchpoints — assessing them from the perspective of the individuals.
In Web1.0, one prevalent means of assessing interactions is via Web Analytics and Web Metrics. I hold the highest respect for two leaders in this space, namely Eric T. Peterson and Avinash Kaushik.
This work, however, is only part of a larger domain of interaction assessment: Design Research. This generic term applies equally to all interactions and related design (online and offline). For some audiences, I also use the label “Consumer Insight” (in E2.0, the predominant ‘consumer’ is the employee).
This model was devised to differentiate key research sources and related activities:
- Transactional Analytics
For online interactions, this typically = clickstream. The clickstream captures the interaction or transaction. While relevant, this data is nearly useless in isolation. It lacks the necessary context to draw meaningful conclusions. Knowing how many people visited a site is not nearly as relevant as why they visited (intent) and how successful they felt they were. Having a heartbeat tells you little about your health.
- Behavioral Analytics
This is the marriage of action and intent. If you don’t know why people are interacting with the business, little can be inferred about their actions. Some transactional (clickstream) tools infer intent — stacking one inference on another — the potential for erroneous conclusions exponentiates. Knowing the intent is also useless without the transaction — there is no way to truly assess the say/do gap (which is often significant).
- Feedback Loops
While most of what we’re talking about here can be considered feedback, this is called out to address two specific goals: gathering data from all the touchpoints and intentionally designing better loops in the touchpoints. This is a huge area of focus: key touchpoints are typically buried in divergent/competing organizations (website, customer service, call center, sales, marketing — for employees, the touchpoints of interaction are less well-defined). Coordinating a total experience and the feedback associated with all touchpoints is a major undertaking. Often the touchpoints don’t gather relevant feedback, they focus too much on ‘resolving’ an issue and not ’solving’ it. The ’solving’ of repeated issues doesn’t happen where there is no awareness. Awareness comes from the synthesis and sharing of the findings.
- Usability Studies
I’m not an advocate of usability studies because they are isolated from many relevant factors, are often laden with prescribed intents, and people tend not to be as ‘honest’ as is needed. If they’ve already been done, leverage the relevant findings. Most real ‘usability’ issues can be identified via the other methods. Usability studies may still be valid for production models that rely on major releases (as opposed to the continuous change of 2.0) or for situations where no other form of research is possible.
- Ethnographic Discovery
One of the best ways to gather relevant context — observing and/or talking to people as they engage in an activity — it can provide rich insight. There is often relevant contextual findings gathered during projects, but it is rarely synthesized/packaged and made available for others (it often gets buried, repurposed as requirements — focusing on the ‘what’ not the ‘why’).
Most companies I’ve been exposed to, either:
- Address none of these to any real degree
- Focus on Transactional Analytics only (e.g. clickstream)
- Focus on some aspect of several, but in isolation from each other
- Rely on ‘market research’ methods (ineffective here)
- Fail to collectively capture, synthesize and leverage the findings
The goal is to bring together relevant facts to inform discovery (the possibilities) that then lead to design — especially adaptive design to support individuals interacting with or on behalf of a business. Such facts are often difficult to find and difficult to effectively interpret and leverage — the barriers to ‘use’ are too high. Lowering these barriers is game-changing.
Various technologies (esp. web analytics) often include dashboards. Such dashboards include relevant data but they often include data focused on Search Engine Optimization and performance, which is of lesser relevance here.
For this model there’s potential for a collection (a dashboard might be one form) with related details and views that continuously offer and highlight new findings across various touchpoints. A more 2.0 approach would bring the facts into the context they’re related to, featuring (draw attention to via teasers) certain findings in tidbits, leading to more detail. Set up as an open ’social’ collection, individuals can share their discoveries and be the storytellers of what they’ve witnessed by both introducing new discovery findings or commenting on the data gathered from the touchpoints: a conversation flowing on the stream of work.
By bringing together the ‘witness’ of both automated touchpoints and human reports, the health of the business machine is given a ‘voice’ — the implicit becomes more explicit, providing a context and a means to:
- Suggest new actions or changes
(inherently different than the ‘idea’ model for innovation)
- Validate proposed changes
If an E2.0 initiative does not include provisions for such context, wherein does adaptation occur? If not adaptive, is it 2.0?
Permalink
Paula,
I am going to return the favor: you are my new best friend. This is an amazing entry, very well written and talking to all the stuff I have been (feels like) preaching for the past 4-5 years. I first wrote about intent as a game-changer back in 2003 while at Gartner. I used it at presentations and people were looking at me with a blank stare (it is somewhat difficult for me to figure out if that is because of my accent or the content) and talking with some of them afterward the comments were that the idea was great — but they had no idea how to implement it.
How to identify intent without perfect knowledge of the parties in the interaction? For example, what is the intent behind the policies an organization creates (we usually assume saving money, but — is that always the case?)? What are they trying to do in the long term when they say (for example) that they can forgive two or three late payments in one calendar year if you ask nicely and you are in a certain segment? Was there ever any correlation proven between forgiving late payments and continuous relationships (notice I don’t use the term loyalty)? This is the intent that even organizations don’t understand but they need to start identifying. The effort that Wim is leading with the Dashboard 2.0 is a beginning to understand the correlations that lead to intent on the part of the organization.
On the other hand, there is intent from the customer (or the community formerly known as customer these days). We used to, for the longest time, to try to understand that intent from what you mention in your post: clickstream analysis. That was the original promise of CRM (remember: first we do transactional to collect the data, then analytical CRM to understand customers better – including intent). It never delivered because there was at least one element missing: what we used to called psychographics before we realized it could not be aggregated in groups, and today we call direct feedback. Getting into the customer’s mind was an issue of simply asking — but most people did not know how. The EFM “revolution” of the 2005-2007 era was an attempt to mass produce feedback. It did not work.
The corollary to this rambling (sorry, I tend to ramble when I get excited about reading amazing insights like this) is that we are now entering the era of the mass feedback (the psychographics mentioned above) but that needs to be merged with everything else: wanting something but not acting on it makes no sense – so we need to mix the wants we collect in direct feedback with transactional data (that was the premise for the CFS model I introduced in 2001 – later called EFM), with existing historical data, with demographics data, and now with community-created data. Put it all together and we could, if we are good an listen well, begin to gleam some inklings of intent in the actions from the individual community members. That is the promise that we can see delivered in the next 2-3 years.
The bottom line: not only are you extremely correct and accurate in your post here — I think that part of what you have towards the end is the beginning of the blueprint that organizations will need to understand to start leveraging communities and social customers.
Thanks for writing this, and even more for reading (if you did) these comments. I know it seems long and rambling, but somewhere in there is the explanation of the epiphany I got when reading it.
Esteban
Paula,
Thank you for this very thought provoking note. As we have already explored briefly, I would like to offer a few thoughts to facilitate a continued conversation on this topic.
First, I am interested in your perspective on how to design “Collaborative Web 2.0 environments” to be more conducive to “real problem solving”. For example, who specifically should define the “real” problems? The “real” solutions?
Your consumer intent concept is also very thought provoking: Is the customer “intent” always clear to the customer? Is the customer intent always clear to the “Enterprise”? If not, what is the best process to clarify the customer intent?
Similarly, does the “Enterprise” also have an “intent”? If so, what is the intent of the enterprise? Is the customer intent always identical to the Enterprise intent. If not, how do they resolve the differences. Also, what is the optimal “intent ratio”?
I am looking forward to your perspective on these issues.
Arie.
@ariegoldshlager
I certainly do
The significance of ‘real’ was my feeble attempt to get at ‘root’. And yet, I hesitate to go there because I get all discombobulated when people whip out “root cause analysis” (which is somewhat relevant but can miss larger systemic failures).
A constant design challenge is deciding where to focus: which problem to solve and how to carve it out of the whole it operates in (differentiating ‘fixing symptoms’ from solving problems). And already language is failing because I could even go back and start arguing counter-points to all of this.
But to finish this thread, because of all the dynamics involved, there’s no perfect problem to solve and no perfect way to solve it and most importantly, at the end of the day, you have to have the resources (including the buy-in and willingness of other people) to get it done. Some E2.0 tools can help facilitate such efforts — tapping the ‘current’ of critical wetware.
Is intent obvious? No. That’s the purpose of the ‘collective’ of observations and the gathering. You have to both ask and observe (thus my note about the say/do gap). Let me offer an example. At Texas Instruments the definition of ‘consumer’ varies moreso than other business models…because the entire cycle involves a lot of different people: designers, purchasing agents, etc. They actually hadn’t looked at the data they had to ‘decide’ who their customers were for which activities, and whether they were all equally relevant or deserving of equal help. The significance of roles/relationships to channels and touchpoints were major. The people who paid the bills (the ‘transactions’) were not the most important roles to satisfy (not to suggest the relationship is unimportant). But they were not addressed at all online (well, not to my knowledge) — their normal interactions were via other touchpoints. The most significant online relationships were with engineers and designers who are ’shopping’ for ‘raw materials’ for their designs. The breadth and variety and focus of interest just among these roles was vast. The online feedback mechanisms were just beginning to paint this picture (and the field research I did just before the end of my contract, brought to light even more potentially relevant dimensions of differentiation).
The best example I’ve ever seen for summarizing some of this (I’ve got a physical copy, I may need to take a picture and post it sometime), is a ‘map’ done at Microsoft for their Dimensions product. Actually there were two. One is differentiated by primary focuses/roles, but also recognized that there were other critical levels of differentiation. While the needs of someone using Dimensions for finance would be fundamentally different than someone from IT, the needs of a finance person would be tremendously different not based on the size of the company, but on the ‘depth’ of the work being done. A small company managing the finances of large companies has very ‘deep’ needs. Getting to the point of being able to create a ‘map’ like this at Texas Instruments had not occurred (and I was ‘let go’ for suggesting that any and all of this should be the focus of the work I was doing — my job was to crank out wireframes).
Will the intents be exact? No, both cost prohibitive and impossible — the conditions are constantly changing, the ‘color’ and ‘flavor’ of intents change. And as the system responds, so do we — our needs change the system and the system’s response changes our needs.
And yes, businesses have intents. They must survive. Resources only go so far. Indeed, it’s all that little stuff that I begin to wonder about at Zappos to decide ‘how’ they push the envelope on some of this and still find a balance on their limits.
The optimal ‘intent ratio’? Again, I’d look at Zappos as an example. The problem is trying to enumerate any of it, because their culture accommodates a lot of the ‘fixes’ (http://gotads.blogspot.com/2007/08/secret-of-zappos-success.html). They minimize classic Marketing and shift the investments to things like CRM. Once you start doing that, the ratio is irrelevant. You’re replacing one for the other rather than trying to strike a balance.
A critical postscript. The overall goal here is to do something this phrase seems to capture better than any other I’ve come up with: “collect narratives around the edges”. Look for the paragraph that talks about this concept in this great piece on storytelling: http://www.grouppartnerswiki.net/index.php?title=Story_Telling_by_Kevin_Hoffberg
There are other great pearls in this piece that I’m hoping to cull out for a related focus, later.
Also, there are very relevant clues in this presentation by Claudia Kotchka as to what else might go into this ‘collection’ — including imagery of REAL customers — LOTS of imagery: http://www.vimeo.com/5203345
I’d also suggest a collection of soundbites — the good, the bad, the ugly. Those are most powerful to grab and reinforce an idea and are WAY more compelling — often making people forget ALL about ROI.
i am taking on ROI next week in my blog. got a three-four part series i am writing this weekend including that… talking about communities, my new found love 
nice video, btw, thanks for sharing…
I’ve taken a broad perspective on Design Research, particularly the perspective of how to leverage/share the results more broadly.
Dan Saffer did a great job of covering the deeper aspects of Design Research more recently: http://twurl.nl/ri52un
What a terrific post Paula. Thank you for pointing it to me, I somehow missed it before. I am of course mostly focused on the Feedback Loops of the continuum and, to the lesser degree, it’s adaptation mechanisms and practices. Unfortunately I rarely, if ever, see any “holistic” or “designer thinking” approach to understanding of “intent” in most corporations therefore most attempts are very interaction point oriented.
Gregory:
If only the corporate approaches were ‘that’ good : ) While there is focus on interaction points, it’s more of a focus on ‘points’ without much concern for the ‘interaction’ (save anything that can be measured and is generally scripted and automated to the point that it’s gone beyond algorithm and it almost human binary code — aka. transaction, vs. interaction).
While the model shows a specific entry for “feedback loops” that was a matter of convenience only. ALL of the parts of the continuum should be architected for a feedback loop component — aka. the conversation, or the evaluation of ‘listening’.
While a focus on Design Thinking is only now gaining broader interest, I’m not sure that the voice leaders in this space have sufficiently told the “interaction” or the “feedback loop” story. Indeed, perhaps one of the strongest proponents of these concepts has not been recognized in Design Thinking circles: Russell Ackoff. That will change.
I’m currently reading a piece from his academic companion, John Pourdehnad — “New Frontiers in a Knowledge-Based Economy: The Influence of Innovation, Design Thinking and Social Computing” [http://www.in2in.org/od/thought/2009-03-ThoughtPiece-Pourdehnad.pdf]
We should compare notes.
» Subscribe to the RSS feed for these comments
HTML-Tags:
<a href="" title=""> <abbr title=""> <acronym title=""> <b> <blockquote cite=""> <cite> <code> <del datetime=""> <em> <i> <q cite=""> <strike> <strong>
Additional comments powered by BackType
