Some of the important learnings from “Unleashing Digital Customer Experience” event (Amsterdam, November) were that for companies, consistency in all directions still remains a significant challenge:
- Consistency across the whole customer journey, especially with the increase of digital touchpoints
- Consistency in internal alignment – how non-CX KPIs correlate with the CX goals and vice versa
- Consistency between brand and customer experience
So in this line of thoughts, brand and customer experience are just two sides of the same coin.
- Brand is all about the promise you make to potential customers – what pains of theirs will you solve, how will you help them better themselves.
- Customer experience is all about what you deliver post-sales and how do you make it come to life.
So in a way, it’s a very simple equation. What you deliver needs to exceed what you promise. But moreover, it’s all about making the two sides of the equation work in synergy. Here are a few examples of the added benefits if you achieve synergy:
Brand to CX
- Brand perception can be seen as a proxy of your customers – both vocal and silent, and how their experience impacts the perceptions of your potential customers. In B2B studies we repeatedly see that the most impactful and favorable channel for brand info, scoring above 70% on both dimensions, is “recommendation from colleagues”.
- Brand studies can help you better identify the emerging needs of your potential market and then use these insights prepare your organization how to deliver on them and proactively prevent customers from even becoming detractors in the first place. An FMCG brand study once helped us identify a new category emerging, which served the needs of current customers better, so the company changed a few key qualities of their products and moved it to the emerging category, achieving better results in the Delivery > Promise equation.
CX to brand
- In return, CX insights can help you draw on your strengths to fortify your brand image. Knowing what threads the needle in CX and using this as a brand strength can be a very powerful driver. In our brand KPIs studies, we have seen that drivers resulting from deep analysis of CX insights are always at the top of the brand image impact analysis.
- Furthermore, knowing who your promoters are thanks to a full-coverage CX program can empower very efficient positive word-of-month and referral campaigns for increased brand preference. In our member-get-member campaign with a B2C sports equipment vendor, we were able to increase referral rates by 60% by identifying and including potential promoters into the program.
- And last but not least, proactively identifying detractors and passives, and turning them into promoters can scale all of these actions up for even higher ROI of your CX, your brand and your data. It’s one thing closing the loop with 100 people, and a completely other thing doing it with 7 times higher reach. It is such a program that helped one of our telco clients increase customer retention by over 30% and keep nearly 4 million euro from churning.
So, how do you create these synergies and what is currently stopping you?
A key hurdle is siloed data. Usually, companies sit on a lot of data that is not fully utilized or is not fully deployed into tactics. Different teams own different parts of customer knowledge and there are a lot of disconnected dots.
Customer experience and brand studies are often two parts of the same coin, yet they can often be managed by different teams with insights sitting in different places. However, brand studies can also be a powerful source of information of your silent customers and how they position your brand in front of their friends, family, coworkers. The knowledge and perception of potential customers about your brand will very much signal potential gaps and unrealized strengths in your customer experience.
We believe that every company should proactively address customer needs if they want to be successful in the future.
True proactivity works on 2 levels:
- Strategic – where you go beyond brand and CX alignment and you are not only reacting to feedback but anticipating emerging needs at scale
- Personal – where you don’t just close-the-loop with dissatisfied customers but predict what a customer is likely to do next and personalize your approach accordingly
The 3 pillars of Brand & CX synergy
So how can you go about achieving this? Our solution: scale your knowledge about existing customers with predictive algorithms, keep consistency across brand studies and have all insights – brand & CX in one place.
And be open to experimenting in order to find out what truly works for your business and your organization.
Scale your knowledge about existing customers with predictive algorithms
A possible to this challenge is a model called Predictive NPS.
This model predicts the NPS or other satisfaction scores of your whole customer base at any moment of time. It shoots up your response rate to 100% and helps you hear the voice of those silent customers, who will never complain but you will still feel their effect both on CX and brand level.
How does Predictive NPS work
In the model we combine multiple data points, such as behavioural data, usage, even financial data and NPS data from customers who have already responded an NPS survey.
And for those who think procuring this data is close to impossible – the good news is that pNPS can also work with the data already available within your CX program, such as demographics and customer segment. This light version of the model is usually deployed as proof of concept and in cases of severe siloed data.
The algorithm identifies similarities of data between NPS respondents and non-respondents to pattern similar behaviors and based on that predict the NPS of non-respondents.
Predictive NPS works in various contexts and industries
We have developed and deployed this model across a number of B2B companies. For example, for one OEM with a stagnant, low response and reactive program, we integrated NPS & CSAT data with complaints, ticketing and monthly ops data of the equipment to score over 10 000 customers globally.
This helped us uncover a previously unsuspected high rate of detractors in a specific segment of customers. We then dug deeper to uncover a structural issue in delivery time estimation, so the company could work on resolving these.
It can also work in retail. We implemented Predictive NPS for the e-store customers of a sports goods brand. We found out that approximately 50% of survey respondents indicated a high Likelihood to Recommend. However, their response rate was only 8%. With Predictive NPS our client was able to identify opportunities to activate referrals as they happen: when a customer order is delivered and they are predicted to be a Promoter, they get an e-mail nudge to refer them to a friend and use a discount code for themselves. Even if 10% of newly identified Promoters send codes to friends and 10% of friends use them, this is still around 4 million of additional revenue for our client.
Key Takeaways
EXPERIMENT quickly with small projects. Find ways to make the most of data you have at hand in your function or department, generate quick wins from the pilot and then dig deeper. Build a predictive model with the data you already have at hand, prove its value and then expand with other types of data to improve accuracy and scale.
TRANSLATE your CX strategy into organizational-wide KPIs and actions
CHALLENGE YOURSELF and look for ways to create fans
Understand your MATURITY and plan ahead.
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