Consumer behaviour is changing at a rate that is faster than most organizations can keep up with. And while embracing new technologies — like AI, blockchain, marketing automation, chatbots, personalization — is championed as the solution by your vendors and service providers, ultimately the majority of those ‘digital transformation’ projects will fail.
Underlying this challenge is that data lies.
More accurately stated, data that has been gathered based on outdated assumptions about consumers that are constantly evolving, will always be inherently flawed. This is not a factor of poor management, it is the result of organizations (corporations, government, or otherwise) being experts at operating, not customer behavioural analysis.
What follows is a Design Thinking inspired innovation blueprint that our research consulting firm PH1 uses to help clients turn challenges into opportunities. It also is the foundation for our CX workshop on April 17th in Vancouver for the Marketing Research and Intelligence Association.
Customer Experience research enables organizations to understand how consumers interact and engage with all touchpoints. It enables a deeper understanding of motivations, pain points, as well as identifying untapped opportunities.
It is our recommended form of research when faced with any of the following challenges:
Ultimately, Innovation is not a technological problem, it’s an adoption problem. That means that the greatest solution — hardware, campaign, product, back office processes, or otherwise — can fail if consumers decide not to adopt.
Targeting Millennials isn’t the solution to your innovation challenge — the persona lacks specificity. Neither is relying on other oversimplifications like demographics, purchase analytics, NPS, or website analytics — they usually lack context and understanding of the individual’s decision-making process.
Surveys in general, including customer satisfaction and NPS open text data, can be plagued by subjectivity of language and bias. I’ll go come back to this later.
Customer Experience research is a fantastic approach for understanding deeper human-centred factors, like motivations, because it provides customers/consumers with a tangible point of reference (the experience they’ve had) to frame a series of questions around. E.g. “What motivated you to sign up for the this program after reading the ‘Why Now’ page?”
To prepare for starting this type of research, it’s important to build interview guides and data analysis around the decision making process, not conversion points. The goal is to understand motivations, expectations, and their sense of fulfillment across their personal experience.
Innovation is achieved by increasing the speed at which unmet expectation can be discovered, met, and delivered upon. To be able to do this you need to see past the obvious backlogged items that will already be expected be addressed via upgrades, iterations, releases.
If you ask a wide range of consumers what they want and why they want, it will be a waste of your time. Surveys and data in general often incorrectly report opportunities for innovation because they lack three key insights:
2. Perceived value (may be measured via prioritization or brand displacement)
3. Quantified value (may be measured via time saved or comparable purchase savings)
While those three insights are the most valuable to the organization seeking to innovate, if it intends to identify and connect with consumers at scale (segmentation) you’ll require a fourth insight:
4. Consumer lens
Innovation is a highly subjective pursuit and the lens is important to understanding how consumers define subjective emotional states like: “loyal,” “frustrated,” “excited,” and “personalized to me.” Understanding their particular lenses enables organizations to identify what binds these types of prospective customers.
Depending on your project you’ll uncover highly individualistic characteristics that bind groups of consumers into human-centred segmentation. For example, in a recent project our team identified “stress coming from a poor work-life balance” as the lens by which a consumer segment viewed a CPG product.
Before you can answer “what do customers actually want out of my organization,” we need to dive deeper into what in their life causes them to seek out the solution your organization is offering (product/service, etc).
The Jobs to Be Done theory looks at this pragmatically from the standpoint that every customer uses a product or service as a result of having a job to be done in their life. When analyzing customer experiences, it’s important to go deeper to understand the challenges faced by consumers.
For example if we asked a group why they use Facebook many would answer “because it’s easy,” yet when you understand their particular lens and dive deeper, the answer can expand to:
”as a Facebook user I save time because it is universally adopted. I can stay more connected than if I had to use email, SMS, and various other tools instead of a single platform.”
Quantitative data is the only way to identify trends en masse, however those methods (surveys, analytics, etc.) lack the robustness needed to answer questions in a meaningful way. What it can do is identify themes worth investigating in more robust manner using qualitative methods or highly-segmented surveys.
How our team gets the experiential insights you are seeking:
Organizations are overloaded with data about what customers interacted with during their experience, but they lack clarity on why. They also lack visibility on the actual experience of anyone who abandoned the experience early on, or those that never tried it in the first place. And in many cases the fringe segments (e.g. those that have yet to use the service) largely outnumber those that they do have data about.
Ironically from the consumer standpoint, scientists like Dan Ariely have discovered that quite often consumers aren’t as rational as they think they are when making decisions.
All combined, this results in organizations having little understanding about the experience customers actually have. And since consumers themselves don’t have clear answers to ‘why’ they make the choices they do, it requires researchers to behave more like scientists to remove bias.
Ultimately we are seeking the following insights:
Researching experiences should be an experience in of itself for participants. This means using methods — like experiments, demonstrations, workshops — as a way of encouraging dialogue rather than short and potentially forced answers.
These qualitative methods also require the researcher to infer, more than ask, and to set up a series of questions that either validates or disproves a thesis. We recommend this obtuse form of research since it can remove inherent bias and false positives.
Researching every aspect of an experience is impossible, that’s why we focus on inflection points that have been identified via data analysis. Those are points of interaction with the consumer that have a significant influence on the quality of experience.
Now armed with an understanding of what customers want and how they actually experience your brand we can begin analyzing the insights. Innovation opportunities and potential disruption challenges are woven between what was said and what wasn’t said.
Adding to this complexity are the constant mentions about emerging technologies, like AI, Blockchain, VR, etc.
Rather than frustratingly trying to force a square peg (new trendy technology) into a triangular hole (your organization’s strengths and budget), we recommend a comparative analysis against a much broader set of peers than you’d likely expect. Then examine an emerging tech if it suits your opportunity.
Innovation isn’t about catching up to a competitor by launching the same product (i.e. Facebook copying Snapchat); it is about finding a new way to solve an old, or new, customer problem (i.e. DocuSign simplifying contracts).
Experiences are time-based activities and should be analyzed in the same way. That’s why Customer Journey Maps are an essential tool for translating customer emotions, motivations, needs, jobs to be done, and much more into a quantifiable artifact. They enable you to see the world as your customers do.
They also are a great competitive intelligence and R&D tool.
The Design Thinking methodology enables our team to turn uncertainty and tangential insights into opportunities for innovation. Legacy thinking is like an anchor, dragging down the possibilities of looking at the problem with no limitations. That’s why startups can grow so quickly — they aren’t hindered by ‘how things are supposed to be done’ and you shouldn’t be either.
Combine these tools to compare customer experiences across a carefully selected list of organizations to identify innovation opportunities.
Innovation doesn’t happen over a two-day hackathon. It requires patience and leadership that is determined to provide customers something exceptional. And depending on your exact business challenge these projects can take several weeks or months — especially if you’re the incumbent market leader.
This process of customer experience analysis will allow your organization to:
Questions? Please send us a message at PH1 Media. And if you’d like to get an accelerated taste of this process, along with recommendations on which tools to use at each phase, join us at 5pm on April 17th in Vancouver for a hands-on CX workshop.