Last week ESOMAR held the annual MENAP Forum in Dubai, bringing together the best in research knowledge and beyond to share cutting edge techniques and strengthen the local industry as a community. RW Connect blogger and Managing Director of our media partner Insight MEA reports on the event.
Without a doubt the research industry is struggling to evolve at the pace of technology innovation as it relates to data and emerging data sources. We don’t have a “big data problem”, we have a distinct gap between our traditional methods and a massive influx of new technologies and data streams. Traditionally we’ve focused on primary data collection, giving little thought to ancillary sources of data- in large part because they simply didn’t exist. Even as recently as 5 years ago, there was limited access to many of the consumer behaviors that can easily be tracked today via digital activity (online, mobile wearables, IoT, etc).
Never before have we seen such an influx of technology driven solutions enter the research space. From text analytics to image recognition software, social media and geo-location data providers, many of the companies to watch (like SocialGlimpz, KnowledgeHound and MetricWire) are being driven by entrepreneurs with limited formal research training. This in fact may be helping, rather than hindering, their success. Case in point, Nick Drewe. Nick keynoted at both the AMSRS annual conference in 2013 and at CASRO Tech in 2014 where he talked about his highly accurate prediction of Australia’s Hottest 100 by using big data from Facebook Shares, Twitter Tweets, Pintrest Pins, Tumblr Posts and Google + Plus’ to predict 92 songs from Triple J’s annual music countdown. Eight of which were exactly correct in their order (including songs 3, 2 & 1!). The data Nick was able to extract from social media and a bit of data modeling, with no formal research training, should serve as a wakeup call to the industry. There is a new breed of researcher afoot who is unencumbered by traditional methods and, in many cases, can vastly improve on the traditional research we’re delivering to our clients, often using simple open source data.
Pravin Shekar gave a brilliant presentation a few years ago on “jugaad”, the Hindi-Urdu word which means the utilization of creativity to make existing things work or to create new things with meager resources (think “hacking” in US terms). Companies in India are adopting jugaad as a practice to reduce R&D costs and maximize resources. What Nick Drewe did to game the Hottest 100 is a perfect example of jugaad in the Western world, and is exactly what we need to be embracing as an industry. Often I hear my fellow researchers criticizing new techniques and technologies – focusing on what they DON’T do rather than what they can ultimately bring to the data party. Kudos to Kantar and Nielsen who are setting the tone this year for what I believe is the future of the industry – collaboration and strategic “acqui-hiring” of technology driven data providers (Kantar, by investing in Zappistore and Nielsen with their acquisition of Affinova). These strategies will be key to the evolution of larger research agencies. Smaller, more nimble firms, that aren’t afraid to deviate from the norm also have a real opportunity to offer marketers hybrid research strategies utilizing techniques that integrate cross-platform primary research with alternative technology and data providers.
Our strength as researchers lies in our innate curiosity and our commitment to delivering insights and, ultimately, a data driven story telling experience – regardless of the data source. Our challenge is determining which “disruptive” new technologies and solutions can provide more actionable research insights. It’s not the origin of data that matters, it what we’re able to do with it.
Kristin Luck is President at Decipher
At this year’s Congress 20|20 Research exhibited their potentially groundbreaking work with the Oculus Rift. Over on RW Connect we were intrigued as to how a company could make the decision to invest so heavily in a technology that has yet to go on general sale. Here Isaac Rogers shares the process 20|20 went through in creating a commitment to virtual reality.
I’ve had the luxury of attending a few customer experience conferences recently and I have to say they’ve been largely fascinating. Hearing organisations talk about their passion for customer service, the efforts they’ve gone to improve it and how its had a transformational impact upon their business – both internal culture and morale, but also the bottom line. What’s also been fascinating has been the choice of speakers. I’m used to seeing market researchers and their clients discussing these topics, but there appear to be some new kids on the block – the behavioural scientists.
I should point out that when I use the term ‘behavioural scientists‘ I may be technically wrong. Every conference I go to they seem to have a subtly changed name – behavioural economists, neuro-scientists and who knows what they’ll be called next week! But regardless of the exact terms I’m sure you’re all aware of the kind of expert that I refer to.
For those of you who don’t, I’m talking about the experts who follow the thinking of the likes of Daniel Kahneman, to study the effects of psychological, social, cognitive, and emotional factors on the decisions of individuals and institutions. This typically integrates insights from psychology, neuroscience and microeconomic theory to explain why we humans appear to act ‘irrationally’ and make choices that when assessed in the cold light of day make little obvious sense.
I’m in absolutely no way qualified to comment on whether the academic work that has gone into this is valid, or not – and have no vested interest either way. However, I do recognise that there appears to be a new understanding of how behaviour is influenced, and how we as customers make our choices. The other thing I recognise is that whenever I hear the behavioural scientists speak, they seem to focus heavily on advertising and brands – the bit they always seem to scoot through is the implications for how we manage customer experiences and the impact these have on customers.
This seems a little odd to me because there’s potentially a huge amount we in customer experience could learn and apply. I’m utterly unqualified to join the likes of Kahneman on this topic, but here’s my attempt at conveying how we can use some of the thinking and principles underpinning behavioural economics to better manage customer experiences. I don’t claim that this is perfect or exhaustive – people could and have written books on the subject – but here’s three key ways in which we can make what we do better by learning from reading some of those books,
Understand the difference between memory and experience
As researchers in customer experience we are regularly measuring the supposed quality of an experience or interaction via the customer’s stated level of satisfaction. Yet, the work of the behavioural economists on how humans remember experiences suggests we need to be very careful in how we approach this. Without going into the science, it seems there are two different mindsets – how we felt during the experience and how we remember it afterwards. This memory is seemingly based on two points – how we felt at the end, and the peak emotion.
For us researchers, this means satisfaction data isn’t reflecting an overarching, considered or balanced view of an experience – its often measuring two moments. Some of you may have spotted that something like this was occurring when looking at results in the past – particularly when you look at what people talk typically about in verbatim or open questions. You may have also spotted that the time between an event and you measuring the satisfaction with it leads to a different score – if you measure it in the midst of an experience you may get a very different result to measuring it afterwards.
In reality this doesn’t mean we researchers need to change methodologies or anything dramatic – our data is as valid as it ever was. However, we need to understand exactly what we are measuring. This may mean we need to look at the results in a different way depending on when we measure the experience. We must also ensure we design our research to measure what we mean to. For example, it may be cheaper and easier to interview customers about an experience up to 2 weeks old, but this will only be useful if you want to measure the memory it formed.
However, there is a potentially huge implication for how we advise our clients. According to this theory, if they wish to create positive memories, they don’t need to excel all the way through an experience. Instead, they need to avoid any moments of pain, create a ‘high point’ then end the experience on a high. Consistency during the experience is no longer king. However, it does raise the obvious question: when is the end of an experience? You must make sure you have the same perception as the customer otherwise your ‘ending on a high’ may well just be a forgotten moment midway through their ‘experience’.
Understand the biases
One of the key things emerging from this school of thought are the biases that affect how we act. The last event I heard listed out 15 of these, but new ones seem to emerge every time an academic looks at this. Obviously this will make it hard for us to be constantly up to date, but its something we must try and keep abreast of. I’m not going to try and review them all here – I’ll leave it to you to do that (and I’m bound to miss one), but one I think we need to be especially aware of for customer experience is the concept of loss aversion.
This seems to be one of the better documented biases and basically points out that human are risk averse. In particular, even when the odds of winning and losing are the same, the positioning of any gamble as avoiding a loss or making a gain has a huge impact on how people react. Considering that much of the work we do in customer experience is actually looking at how experience affects loyalty – and how often do we see inertia preventing customers leaving a brand they clearly dislike. Understanding loss aversion – and how to overcome it – has a huge potential for helping our clients to either keep their customers too fearful to break away, or overcoming the fear of the unknown that prevents them switching to your brand.
Practically, this may actually mean helping our clients understand the extent to which loss aversion (or other biases) act as limiter on specific customers – or identifying the circumstances where loss aversion no longer limits. To give you a genuine example of this from my own work, a study I ran found that mobile phone customers with access to an alternative network to theirs – through either a second (usually work) phone, or through another household member were significantly, and substantially, more likely to a) switch their network when their contract expired and b) move to the network they were exposed to. I can’t prove it for certain, but I suspect that their exposure to the other network was reducing their loss aversion; they knew what they were getting so were confident to change. If that pattern is copied elsewhere we may find that the best way to help our clients retain their customers is not to give them better experiences but to simply stop them having experiences elsewhere!
One of the basic findings of Kahneman (and others) is that the human brain operates as if it has a slightly dual personality. Specifically ‘System 1’ which makes many of our decisions immediately and instinctively based on whatever information it has to hand, and ‘System 2’ which makes slower, more considered decisions. We wouldn’t be able to get through life without ‘System 1’ – imagine having to weigh up the pros and cons of every action before you can act – at 10am you’d probably still be deciding which pair of socks to wear!
However, System 1 is so effective because it works off heuristics – simple rules of thumb it has developed over time. And, linked to this, the human brain tries to minimise the resources is needs at any given moment. What this means for our clients is that their customers will behave as creatures of habit – they won’t spend time agonising over whether to call or email – they’ll just do what they always do. Similarly, if an experience matches expectations, they’re unlikely to really notice it. Only when it differs will they ‘switch on’.
Furthermore, once an idea is ensconced in a customers mind, they are increasingly likely to believe it and anything which aligns with it – for example if they think your call centre is rude and that your product is poor, that perception will persist and be reinforced by others saying the same thing, even if its not true. In fact, they may even subconsciously reinterpret what happens to fit their view of your brand.
This of course can be overcome – but it takes time, repetition and powerful experiences to rebuild the memories and habits. Changes to an experience must therefore be noticeable (assuming they are improvements) as well as making things better if they have an impact. How you do that will vary, but exciting the right emotions is a pretty good way to start.
Hopefully this brief ride through some of the key points of the behavioural economics theory has been helpful (if not exactly exhaustive). We are clearly approaching a point where we have a far better understanding of how customers behave than ever before and have the opportunity to help our clients make real gains through focussed actions which tap into how their customers think (even subconsciously) and behave. There’s much more work to be done, and as researchers we need to ensure we have our fingers on this particular pulse – but if we do, we can be far more effective than ever before. We’ll need to keep ourselves up to date, and there may even be a few dead ends, but this opportunity to be far more impactful and keep research at the forefront of our clients’ businesses.
The views expressed in this blog posting are the author’s own, and do not necessarily reflect the views of TNS, nor of its associated companies.