The number of possible touchpoints with an organization has grown exponentially over the last few years. There can be direct and indirect sales channels, stores, CS and most of all the incredible impact of mobile technology. Limited not just to app stores but also mobile reviews written through specialist review websites or even store reviews written on Google Maps.
But all this feedback comes in different shapes and sizes. Some of it is unstructured, some of it structured, some could be the length of an essay, some just a word or two! This complexity makes it hard to collect and harder to analyse and build any form of actionable insight.
But one thing is definite: if you manage to do this and analyze this data, you will be a step closer to having a complete customer experience analyzed. Furthermore, this can drive the insight that will enable you to create the perfect customer journey, leading to higher customer satisfaction which in turn leads to better business results. We call this a 360-degree customer feedback analysis: customer feedback from all stages of the customer journey, collected, analyzed and turned into actionable insights.
Why is this radical? It’s a major departure from most current methodologies. Until recently, customer feedback collection and analysis was a fragmented effort, sometimes even split between different parts of an organisation with customer services collecting some data, sales gathering frontline feedback and marketing doing research and so on. In some ways it’s never been easier to encourage customer feedback- this article gives 20 different ways of collecting feedback at different points in time. The result is that you end up with multiple points of view and metrics and lots of data. However, because of this mass of data, it is often difficult to get what you need to make strategic decisions. For this, you need a single point of view, where somebody can put together the big picture.
See how the world’s most customer-centric brands are using Wonderflow on our Use Case page.
A study conducted by Harvard Business School found that an increase in your online rating of just one star can be tied to a 9% increase in overall revenue. So why is it so hard to do? The way customer experience is often addressed tends to be fragmented and inevitably flawed. For example, NPS is a well known metric and is widely used in both B2B and B2C markets. And yet, as this McKinsey article captures, its very easy to have positive NPS and strong metrics at each touchpoint and yet still experience high churn and overall customer dissatisfaction.
Why? Because service delivery is often siloed and measurements only take place at the touchpoint. There can be good reasons for this – it builds experience, it is highly efficient and manageable for executives. However, it’s not the way customers see the world. Even a product query or phone call to pay a bill is part of the customer journey- every customer has a context. The customer journey is the big picture. Due to the fact that, each interaction takes place within the customer’s personal context, the online reviews and feedback can be dismissed as being uncontrollable.
Suddenly it’s clear, that to understand the reasons behind feedback we will need to analyse the customer journey- and 360 customer feedback is key to this.
The customer journey consists of a number of different steps (see image 1 below). Each step can itself be a multifaceted experience but it will ultimately lead to a complete customer feedback analysis process.
For example, the investigation stage may involve online research or visits to physical retail environments or even an online chat about product features. At many of these stages, data will be collected or read. In combination with a great number of touchpoints, we can identify the first challenge: how can we collect and organize all the data from all these sources?
Image 1: 4 phases of a customer lifetime journey
The solution requires technology of course. Reflecting the complexity of the problem it requires a solution which can interact with each other seamlessly. There are two initial stages worth breaking out:
- Data collection: this can be through API technology/connectors, scraping data from the internet, import data sets from elsewhere. It may even involve a manual drag/drop!
- Data preparation: where you put all the data in your data warehouse and prepare it for analysis through cleaning it and unifying it.
The final stage is a mixture of both technology and one of business processes. How do you interpret all the data and turn them into insights? Which feedback is relevant? What are the topics you have to work on and what actions could you take? Companies that manage to get through the first hurdle of collecting and analyzing, face a huge challenge in turning the data into information. Or even actionable insights.
Wonderflow’s own case studies make a useful starting point for anyone wanting to understand our approach and how we aim for a holistic, complete 360-degree view.
We’re not alone in thinking like this. In a powerful TED talk, ‘The human insights missing from big data‘, by Tricia Wang explains that the $122 billion big data industry actually means nothing without qualitative human insights. From her research position at Nokia, she saw the phone company tank by not listening to what their customers actually needed and anticipating approaching trends.Another great transformative example was McKinsey’s City Voices project, which captured Brazilian citizen’s thoughts of daily frustrations but also hopes and dreams through 150 different metrics. It then ran a sentiment analysis to help political leaders understand how constituents live and what they need, in order to better inform public policy. A major discovery was that the most impactful way of improving daily life would be to invest in improvements to urban bus systems.
The key here is how they developed the insight: sentiment analysis. This is the process of analysing online pieces of writing to determine the emotional tone they carry. The science behind sentiment analysis is based on algorithms using Natural Language Processing (NLP) to categorize pieces of writing as positive, neutral, or negative.
The algorithm is designed to identify positive and negative words, such as “fantastic”, “beautiful”, “disappointing”, “terrible”, etc. This, however, isn’t always that easy. Language is complex. People write in dialects, using slang, sometimes with bad spelling. Additionally, they write complex sentences with double negatives or sarcasm: “The product looks wonderful but battery life isn’t that great.”
Understanding what customers are saying is just a step to understanding what they are wanting. Again, it’s a way of getting to the customer context. Sentiment analysis looks for patterns within the data- these can be matched to customer groups who can then be either tracked over time or perhaps communicated to. The endpoint is to tell you more about your customers and their lives and how you impact them- a full 360-degree view.
There are mainly two types of companies: companies that are product-centric and companies that are customer-centric. The first group builds a competitive advantage on product features. That does not last long and is easy to copy so they end up spending a lot of cash on trying to continually innovate. History is littered with the names of organisations who couldn’t innovate fast enough or protect their innovations once they are released. Customer-centric companies build their competitive advantage on relationship-expertise. This is sustainable and hard to copy because it ultimately becomes an actual two-way dialogue with your customers and it’s built into real business processes. It’s far more than just being able to answer the phone or respond to a tweet. This saves money on customer acquisition, reduces churn and allows you to target product development with precision- because you can anticipate what’s valuable to customers. Only with the full view can they make decisions based on the needs of your customers and build products/services that relate to their needs. This is a constant top-down/bottom-up process that affects all departments within the company.
The endpoint? This could also be radical. Unlike the customer’s journey, which touches all areas of the business, a manager’s time and energy is largely devoted to improving a single part of the organization. Should all manager’s work be organized around customer impact rather than functional expertise? It will definitely mean changing your mindset as an organization.
Analyzing multi-language customer feedback in large volume from different sources is a complex process. With an AI-based technology and years of experience, Wonderflow is helping global brands to become customer-centric. Find out more about our solution.
We can’t tell where it might end. We do know that customer-centric companies are more successful in the long run. Additionally, to become customer-centric you need the integrated, holistic 360-degree feedback view. Until recently this was incredibly hard to do- it was a challenge in terms of technology, in terms of scale and in terms of the will to actually do it! More and more organizations are now realizing that without a true holistic 360-degree view they are missing most of the critical conversations with their customers.
Wonderflow empowers businesses with quick and impactful decision-making because it helps automate and deliver in-depth consumer and competitor insights. All within one place, results are simplified for professionals across any high-UGC organization, and department to access, understand, and share easily. Compared to hiring more analysts, Wonderflow’s AI eliminates the need for human-led setup and analysis, resulting in thousands of structured and unstructured reviews analyzed within a matter of weeks and with up to 50% or more accurate data. The system sources relevant private and public consumer feedback from over 200 channels, including emails, forums, call center logs, chat rooms, social media, and e-commerce. What’s most unique is that its AI is the first ever to help recommend personalized business actions and predict the impact of those actions on key outcomes. Wonderflow is leveraged by high-grade customers like Philips, DHL, Beko, Lavazza, Colgate-Palmolive, GSK, Delonghi, and more.
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