Traditional customer surveys are on notice. We’ve reached a pivotal moment in our industry. In this article I explain the reasons why, and explore some of the steps mature businesses are taking to embrace advances in natural language processing (NLP), natural language understanding (NLU), machine learning, systems and data integration to evolve their VoC programmes. We end with questions to help you think about how AI capabilities and automation can enhance your programme, and an intriguing lesson from Fujitsu. First, why are surveys as we know them fading?
Innovation is the elixir of good CX design. VoC programmes play a crucial role in driving customer experience, loyalty and revenue growth. And yet, for all the advances in technology, many businesses are still hooked on surveys. They tend to be fixated with the ones that create easy-to-measure metrics – NPS, CES or CSAT. Executives diligently pore over the results every month. Positive CSAT scores are often mistakenly conflated with an increase in customer loyalty. Negative scores, or a dip, then they’re often unable to pinpoint root causes. But, surveys like these are only a moment captured in time. NPS, for example, is only partially effective from a transactional viewpoint. Leaders know this type of static, 2D customer feedback has many more limitations.
How many customers relish the thought of yet another survey to complete? Surveys are reactive and high-level. Where’s the scope for trend analysis or predictive modelling? Real-time application is minimal. Many businesses struggle to demonstrate any link between customer feedback with business outcomes. At worse, surveys just become a tick box exercise. (Fujitsu is a good example of a company that does things differently – find out how, later). It’s also key to understand that no survey standing alone is effective, As obvious as it sounds, there are still companies learning that they need to collect and analyse feedback from different touchpoints.
Tomorrow’s VoC platforms
Leaders are seeking ways to reduce their reliance on traditional surveys and are investing in AI-powered solutions. Gartner predicts that within three years, 60% of organisations with VoC programmes will supplement traditional surveys with conversation analytics.
Yet, its research last year on enterprise VoC platform adoption found that only about half of all businesses (51%) operationalised customer feedback (see above graph). CX leaders are creating big open spaces between themselves and businesses with feedback stuck in databases and silos. This is not news. But the problem with operationalising data still persists.
Operationalising customer feedback – lessons from A1 Telekom Group
A1 Telekom Austria Group uses sandsiv+ to manage multinational and multilingual CX projects. The Group is one of Central and Eastern Europe’s largest convergent-communication providers. Omnichannel direct, indirect and inferred consumer feedback is collected. Unstructured feedback and data from multiple data streams is analysed in 7 languages. Automated workflow means 1,000 employees have immediate information at their fingertips to close the loop. Feedback is operationalised and CX insights are shared across the entire A1 Group.
Learn how a practical closed-loop approach changed A1 Telekom Austria Group’s CX in this compelling panel discussion.
GenAI is early stage – but it’s changing the game – here’s how
Supporting customers at every stage of the journey – Gen-AI surfaces insights from feedback to enable agents to better understand and support customers at all stages of the journey, make smarter decisions and respond in a targeted, personalised way.
Closing the loop in real-time – omnichannel, real-time insights can be used in the moment to close the loop.
Proactive, empathetic interactions – NLU and machine learning can help businesses better understand feedback. Technology can isolate emotion and sentiment in real-time for agents to respond with empathy.
Leveraging predictive insights – many models already identify patterns in customer behaviour, sentiment, and emerging trends to help teams personalise experiences, predict future behaviour, issues, and action plan. GenAI will only improve customer understanding to help organisations make decisions at a pace we’ve not seen before.
Disseminating cross-functional insights – AI can identify patterns, sentiment, trends and themes from vast data sets and disseminate insights in usable ways to stakeholders across the business.
Re-inventing surveys – AI-powered conversational surveys are less formal, and shorter, than a traditional survey. The ‘ask’ is softer and conversational AI makes the chat feel more ‘natural’. Completion rates are higher than traditional surveys. The Reputation platform, for example, includes survey functionality. AI routes questions in a logical direction. If a customer references a service complaint, then the next question is about customer service matters.
Preparing your business
Is your business thinking about how to enrich your VoC programme through AI and automation? Here are a few questions to help you prepare.
- Goals and KPIs – what are your goals and which metrics should you use to measure to track and evaluate outcomes – for the customer, your people and the business?
- Target audience – this is obvious, but it’s worth revisiting your customer personas if you haven’t done so recently. Your customers, what they value, their preferences, expectations and the channels where they express feedback will have changed in the past few years.
- VoC design – wrap senior leaders from across your business around your VoC programme and involve people at all levels in the design and development. Do you need to revisit journey maps to better understand touchpoints where customer feedback would help you improve a specific experience. Are there gaps in your data sources? Does every department get the information they need? Is your frontline team equipped with real-time insights? Experiment and iterate. Ask your customers and employees for feedback.
- Platform integration – how well does a VoC platform integrate with your CRM and would machine learning and analytics engines tie back to your customer profiles?
- Employee experience – how do you engage and empower your people? Everybody knows there’s a real fear that AI and automation will replace jobs. With the right training and engagement, and then by experience, employees quickly see how AI and automation improves their job, equips them with the insights they need to better serve customers and reduces manual tasks.
- AI training zone – how do you ensure your AI is developed and trained on quality data?
- The human touch – how do you get the balance right between human, and machine interactions? Your customers still expect conversations with an empathetic real person.
- Ethics and compliance – how does you ensure the way you use the technology is compliant, ethical and responsible? How do you eliminate discrimination or bias?
Over, but not out … a lesson on survey optimisation from Fujitsu
Remember I mentioned Fujitsu earlier in the article? The company has been on a transformative VoC journey. Fujitsu recognised that it needed to fill the experience gap by gathering the voices of customers and employees. The VOICE Program was created in 2019 to close these gaps. In rolling out the initiative, Fujitsu made two changes. It replaced CSAT with NPS and introduced a global survey, shifting from a regional approach.
Fujitsu’s utilises Qualtrics Voice of the Customer survey to collect and analyse customer (and employee) feedback. A single platform makes it possible to share and utilise feedback from customers around the world. Survey results are routed to individual, and mutiple, regions, where appropriate to drive improvements. The company can now see a positive link between customer feedback and loyalty and performance measures such as profitability, contract extensions, account growth, sales wins and renewals.
Tip: Fujitsu advises you should aim to survey customers responsible for at least 80% of your cross-portfolio revenues. (Discover more here).
To conclude …
Traditional surveys are reaching their ‘best by’ date. VoC platforms and tools are responding with disruptive GenAI capabilities to analyse omnichannel audio, video and text. By investing in the technology, your people will be equipped with valuable insights to have more intelligent / data-driven customer conversations. Customer feedback is routed to the right person / team at the right time to close the loop. Predictive analytics means teams are able to proactively meet customer demands and action plan using evidence. Efficiency and productivity is improved, costs are reduced. AI and automation is re-invigorating VoC, which has been too reliant on traditional surveys, sluggish, manual processes and sporadic, disjointed insights. The potential to transform your CX and EX is there. But the challenges and concerns must be addressed.
Ways B2B companies can achieve CX transformation
Gartner Predicts by 2025, 60% of Organizations with Voice of the Customer Programs Will Supplement Traditional Surveys by Analyzing Voice and Text Interactions with Customers
3 Ways to Use Voice of Customer Data in B2B Marketing
Aviva Life Reimagines Vulnerable Customer Experience with Verint Speech Analytics
Fujitsu wins Gold for CX Transformation at the European Customer Experience Awards
The VOICE Program, a new management indicator collected from the voices of customers and employees
A1 Telekom Austria Group