You are not just a number
When you combine the ability to measure what matters with the right datasets you find yourself in a different realm.
Banks care about what their customers think. Sure, it’s easy to think about Gordon Gecko, Jordan Belfort, even the Monopoly Man, but surprise, that’s not your bank.
It’s pretty black and white here. In order for any business to stay focused on financial performance, they need to stay focused on their customers. Do you know who is really good at staying focused on their customers? Like, “better than everyone else” kind of good at it?
We know for a fact that six of the biggest investment and retail banks in the world use some the same cutting edge tech for consumer research. Across Australia, we can name just as many household names in the financial services sector across Australia (not just the obvious). We work with a lot of them, and if we don’t, we work with the agencies that work with them.
So what does that mean?
Well, it means that you, their customers, are super important.
Take a step back.
There was a research revolution over a decade ago and even today so many large agencies and brands are still playing tech catch-up.
This is not their fault. They have had their “trusted” partners telling them for years that the tech doesn’t exist, doesn’t work well or it’s a pipeline dream. Ignorance has been bliss.
Technology advancements paved the way for evolving traditional market research and insights gathering to better understand customers. This changes the way marketing leaders and C-Suite can approach and leverage consumer insights.
Traditional methodology by no means falls away. It has its place. This is more about capturing lighter, more efficient insights, more accurate and unique insights that have previously been missed.
Custom research often focuses tightly on the business’ own perceived marketplace and not the market in general. You are talking about framed questioning from a sample you hope represents your customers.
Then you have syndicated research. It’s cheap and quick, but not often anywhere near relevant enough to truly understand your specific customers.
Are you being fed this by your team or even still doing things this way?
Times have changed and the ways people consume products and services has long changed from the halcyon days of the 90’s and it’s 28.8 kbp/s dial up in a world pre-Google.
That’s no iPhone. Apple was launching the “Power PC” and taking investment from Microsoft.
No relying on the internet on your phone. No relying on shopping online. No relying on news online. Definitely no online banking.
Technology changes the way we consume products and services and this obviously started quite a while ago as the internet landed in people’s homes and pockets.
It’s ultimately the same reason why most kids will never ever pick up an Encyclopaedia Britannica or never be able to not afford one.
With that tech change, advertising changed, customer data changed, customer interactions changed.
There has long been a better way of combining unprompted customer insight in HUGE volume, enterprise held data, AND the richness of prompted insights (insert our much loved traditional research here).
The best banks figured it out ages ago.
These banks figured out quite a while ago, that you have the ability to instantly gather and combine more relevant consumer data which you can transform into customer insights.
The ability to funnel billions of conversations to pinpoint the key issues that impact a brand; on/off channel. direct/indirect, upstream/downstream supply chain.
The kind of opinion that says “Hey you need to step up on your customer service or find a new process”.
The opinion that is going to drive crucial innovation to retain or drive new business from competitors.
The very opinion that can turn the dial quickly on brand reputation across social issues and good corporate citizenship.
We are talking about customer and partner research… and using the very best modern tools available.
So back to why banks would even care what you think and what they use.
Like any business, banks want to make it easier to access their products and services as it’s linked to retention. That’s every smart business. They want to uncover unknown demand they can supply. Improvements that make your day-to-day life easier. Whether it’s that change to your banking App or home loan application process. The things you are saying you want and don’t want in your life. A satisfied customer is not going anywhere else.
To do this, banks aim for continual improvement on customer satisfaction by listening to what you think. Most do this through the holy grail of NPS. Whilst highly relevant, it is only a single dataset and lacks in its ability to direct specific change, or draw insight from across the entire customer journey on its various paths to purchase. One might even argue, feedback can be skewed to bias from specific or limited customer interactions
It comes down to the data
Over time, people have separated the idea of what is traditional data (media or other) versus social/online to protect and validate their work.
But ultimately, any research mix is either numeric, linguistic, or visual. That’s all it is. As researchers, we have to be data-agnostic and should choose to use the whole lot. This used to be almost impossible, but today the best practitioners are laminating data sets to get a much fuller picture of engagement and opinion of consumers of products and services.
AI is not just a buzzword of tech companies selling you a pipe dream.
AI-powered technology for categorising ANY media has been around since 2008. That’s over a decade ago. so you can easily imagine just how much it’s matured and evolved since then.
Algorithms which can process language (natural language processing), analyse images (deep learning and neural networks), and identify patterns based on rules you define (machine learning).
Yes. Math nerds gave the rest of us mere mortals the ability to create some pretty special custom formulas which let us categorise language in different ways. For the marketing nerds more relevant measurement was a game-changer because all of a sudden you could custom categorise anything in text; any media, news, social, forums, reviews, questionnaires, surveys, even good old NPS.
Besides, AI sounds way cooler than ‘complex mathematics’.
Who said you never need maths?!
Marketers got empowered with an all you can eat buffet of fast and accurate qualitative insight reporting. As much as they want whenever they want. An analyst taking four weeks coding a sample of 1000 news articles turned into minutes categorising millions of public conversations and opinions online.
However the challenge still remained of poor research design. The same assumptions and errors flawing traditional research can easily stain social and online data. Modern analysis still needs just as much attention to the structure of the research and incorporation of the data sets available.
A poor approach to social research in this space is compounded, as historically, social media had long been the corporate ugly duckling, either misunderstood as a ‘single thing’ for private conversations between family and friends, or as a vanity project of others.
Social media use lacked recognition as an open forum, filled with many different public spaces where people volunteer and share opinions online about how they consume products and their customer experiences. It offered an incredible amount of public discussion. All it just needed to get opinions moving, was to be filtered correctly and categorised intelligently to be analysed,
You need the right tools in the right hands.
When you combine the ability to measure what matters with the right datasets you find yourself in a different realm. We’re talking about AI tech using public conversation from official data partnerships with Twitter, Facebook and Reddit to make sense of opinion. We are talking about feeding in your own community management and customer interactions to trend key insights from conversations your customers are having with you in exactly the same way you would any comment about your brand on a news post, or mention in a popular blog.
In the ‘new’ way banks, agencies, and global brands have long been approaching consumer insights and evolving traditional market research (not replacing) to better understand consumers. Customer profiling has gone beyond labelling a persona with demographics for audience precision. It’s less about the who, and more the what, why and where in the world of journey profiling where intent, the questions asked, and experience along the way that paves the path to purchase.
Oh, and in case you thought the data wasn’t strong enough, the social analytic tech in this space can incorporate your search, e-commerce, data visualisation and community management to give you a complete picture.
Get closer than ever previously possible to a single source of truth.
So close you can taste it. This is why this type of advanced media analytics technology is used by the banks most successful at engagement and customer satisfaction. The best ones use it organisation wide, across community management, crisis management, content strategy and understanding of brand reputation.
There are seven elite Twitter data partners in the world. Your ‘media monitoring’ company is not one of them and there is a clear reason so many are repositioning as social ‘leaders’ to remain relevant. Is that your provider lately? If so, start taking a closer look at the expert social analytics options out there with tech over a decade ahead. They cover off the 24/7 digital world with more speed and accuracy, but more importantly, empower your qualitative research and offer a clearer lens on how your brand is actually perceived. In the end, if you’re going to invest hundreds of thousands or millions of dollars in any message/brand/product, and you are solely relying on the opinions of journalists (online and/or traditional), or even the good folk who provide feedback with NPS, you’re not even rolling the dice.