Running your organization without the aid of customer insight technology is like asking a man to swim across the sea. While he might be able to swim a few miles, his progress barely made any significance in the vast sea of data.
On the other hand, operating with the wrong technology is similar to giving that man a boat. At first, it will seem efficient and effective. The man is crossing the ocean five times faster than he was when he was swimming. But a small boat is no match for the big ocean. You will soon realise that you don't have the equipment and the right tools to tackle the sea, and thus, you're unable to reach your desired goal.
While monitoring and analyzing customer data is crucial to your business success, finding the right technology to do it can feel like you’re swimming against the current.
Many text analytics tools sell the dream of understanding customer feedback at-scale. More often than not, you’re still training that software to look for what you think is important - those known knowns. What you should do is also be proactive about those unknown unknowns to improve your CX initiatives.
As Tricia Wang argued in her 2016 Ted talk, human insights are always more meaningful than the big promises made by "big data";
“Once you predict something about human behavior, new factors emerge, because conditions are constantly changing. That's why it's a never-ending cycle. You think you know something, and then something unknown enters the picture. And that's why just relying on big data alone increases the chance that we'll miss something, while giving us this illusion that we already know everything.”
Nokia, for example, spent billions of dollars trying to understand what their customers wanted from a cell phone. Unfortunately, they collected the incorrect data and falsely believed customers still wanted bulky brick phones. However, the truth was, their customers preferred the sleek and innovative design of iPhones. And today, Nokia barely has its foot in the smartphone market. They have 0.7% of the market. Apple, meanwhile, controls roughly 14%.
So how do you make sure that you’re investing in the right customer insights platform?
The basic principles you should be aware of are as follows:
- ROI: Does this platform reduce the amount of time analysts spend manual coding, tagging/categorizing feedback? And importantly, does it scale well as feedback volume increases?
- Search vs. discovery: Does this platform identify emerging issues or do I have to tell it what to look for?
- Storytelling: How does this platform make it easier for me to communicate customer insights to executives that don’t live in this world 24/7?
Let’s unpack what this means by looking at five key requirements to be aware of when buying a customer insights platform: .
1. Increases efficiency
If you’re like many businesses, you might have discovered that the traditional form of text analytics is largely insufficient and inefficient. We’ve previously talked about the differences between a search vs. discovery methodology here, but for a quick recap:
“Traditional text analytics approaches are using a search based approach. You tell them the codes you want to find and train the system how to go find them. You’re searching for known knowns. The alternative I described is a discovery based approach. The technology tells you what you need to know, capturing the known knowns, but also the known unknowns and, most importantly, the unknown unknowns.” - Ryan Stuart, Founder & CEO @ Kapiche.
Insights teams are actually spending three times longer than they should by manually coding their customer feedback. This is highly inefficient. That time could be better spent identifying the drivers of customer behavior so your organization can design better customer experiences.
Instead, look for software that does all the heavy lifting. This means that it automatically codes your customer feedback, but in a way that supports the discovery methodology. Plus, your software should integrate with other systems, like your CRM, survey platforms, cloud storage providers, and the like, so you’re spending less time switching between each.
This way, you don’t have to spend days or weeks reading feedback, and guessing what information is relevant enough to encode or label.
2. Eliminates human bias
There’s no way around it - customer feedback data is prone to human bias.
Take JCPenney, for example. In 2012, they decided to revamp their store to be more competitive. However, instead of asking their customers what they could do better, they made their own assumptions. First, they focused on collecting data from their younger, trendier audiences—believing this was their only buyer persona. Second, they thought that because these audiences were trendier, they didn’t care for holiday sales. As a result, the data that they collected only confirmed their biases, instead of having objective data that showed them the bigger picture.
The result? Their sales dropped by 25% that year. Plus, they experienced high customer churn as they neglected their oldest, most loyal customers. Assumptions kill growth opportunities.
How can you prevent this from happening to your organization? Use software that leverages AI to support a discovery first approach for customer insights.
With the right technology, you won't be limited to just those known knowns, but also those unknown unknowns.
3. Identifies key behaviour drivers
Most text analytics technology isn't equipped to understand the context behind customer feedback. This is because it's only programmed to analyze how often a particular keyword or topic appears in the dataset. Not only that, but it also ends up simplifying open-ended customer feedback to mere data points.
Open-ended feedback is such a powerful customer insight tool because it gives you the reasons behind consumer behaviour and preferences. Organizations that collect huge volumes of customer feedback often shy away from understanding the ‘why,’ because doing so involves reading individual comments. This presents an impossible binary between random sampling (but potentially missing the bigger picture) vs. reading everything manually but wasting weeks doing so (and also potentially missing the bigger picture because they’re fixating on certain themes/issues they assume are important).
For example, you’ll receive high-quality insights asking an open ended, unstructured question, such as: ‘How can we improve our services?’ or ‘How was your experience with [BRAND]?’ Just asking for a score misses the point of collecting feedback in the first place.
For example, what if cart abandonment is rising on your eCommerce platform. After reading comments from a website visitor survey, you discover it’s because they couldn’t press the checkout button when shopping on their mobile phones. A simple fix to the mobile version of the store immediately unlocks 23% more sales next quarter.
This is exactly what happened to the French football club Paris Saint-Germain. They realised that a lot of their customers weren’t purchasing tickets from their website but couldn’t understand why. After calling their customers and asking for feedback, they discovered there was a bug in their system that prevented customers from using the search function. They soon realised this was costing the club £350,000 a week!
With the right technology solution, you’ll be able to dig deeper into the ‘why’ of your customer feedback to understand that bigger picture.
4. Supports effective storytelling
We already know storytelling is fundamental to successful marketing. It boosts engagement, improves brand recognition, reinforces customer loyalty, and thus, increases revenue.
However, it’s difficult to effectively tell your brand’s story when you don’t know your customer needs and how your product can fulfil that need. In fact, the number one reason that startups fail is that they fail to understand their market’s needs.
Your customer insights platform plays a critical role in connecting non-customer facing members of your organization directly to the customer (but at scale). That's why insights should always provide actionable insights, however it’s always up to you to communicate these clearly and concisely. Executives won’t understand what you’re advising them to do next if they’re lost in NPS scores or endless customer quote slides!
5. Centralizes your data
Centralized data is useful when it’s in the right hands - ie. the customer insights team. Forrester recently reported that most enterprises fail to use 60-73% of data for analytics. That’s a lot of valuable data needed for understanding next steps.
Unfortunately most organizations don’t have the right tools to make sense of all the data that they’re collecting. Not only that but because the data is so complex, people who aren’t analysts end up having sole access to it. This creates a devastating silo effect where critical insights fail to reach those who actually need it. Insights should always sit above all that and use a centralized data warehouse to glue the whole organization together.
Get the technology that answers all your needs
With 58% of companies experiencing a boost in customer loyalty by implementing customer analytics strategies, leveraging insights tools is vital to your business success. However, finding the right one is easier said than done! The wrong tool can quickly take away valuable time, money, and resources from your organisation. Worse, it can be the reason for your company’s downfall like what happened to Nokia and JC Penney.
That’s why you need to have a thorough understanding of what the right tool can do for you. Kapiche gives customer insights teams the tools to make sense of customer feedback with a discovery first approach. In addition, customer insights benefit from:
- Decreased time spent finding insights
- Reduced human bias allowing you to see the real and emerging issues
- Identifying key behaviour drivers so your organization creates winning CX initiatives
- Supports effective storytelling so everyone outside of insights understands what they need to do next
- Centralizes your data so you’re making the most of it.
To see it in action, watch this demo video.