Reshaping traditional client listening

Before the pandemic, client listening was a periodic and decentralised process. For some firms the focus was on key account interviews, for others it was on annual surveys. Alongside these formal processes, informal feedback was shared while doing the work.

The process was focused around helping individual fee-earners to confidently say "I know my clients". For a long time this was the best approach. 

Decision-making during the pandemic revealed the big blindspots this traditional approach created. Decentralised and periodic feedback couldn't inform the agile decisions that Boards were needing to make. As services and processes digitised, decision-makers needed a flow of fresh and relevant insights from their clients, markets and people. How are you doing, how are we doing and how are our competitors doing became the 3 most common questions.

Now AI and modern databases are making it possible for firms to maintain this insight flow in a more sustainable way. The databases enable formal and informal feedback to be stored and accessed centrally. AI, and specifically Natural Language Processing, enables large volumes of unstructured text data to be instantly analysed.

That probably sounds nice, but a little nerdy. So here's three ways that technology is reshaping traditional client listening:

Have you ever struggled through a long customer survey, full of multiple-choice questions that didn’t let you share what was really on your mind? In the past, these questions helped firms avoid the cost and time-delays of manually tagging unstructured text data. The trade-off was that firms only heard about the things they chose to ask about.

A form of AI called Natural Language Processing (NLP) has changed this game. You’re now free to ask open questions, just like in a conversation, and the text comments get analysed instantly and automatically. 

Just two questions - “what do we do well?” and “what could we do better?” - can shorten most client surveys while giving clients the space to share their experiences and what’s currently on their mind. The NLP algorithms scan every comment looking for thousands of relevant themes, emotions, and keywords so you can keep up with evolving client and market expectations.

With AI automatically analysing the growing feedback volumes, client listening becomes a continuous process, rather than a periodic project. This in turn enables you to reimagine what "feedback" looks like. From pitch debriefs and on-boarding experiences, to emails and informal comments, through to reviews and relationship interviews. Feedback can now flow from all stages of the client journey.

Why is this important? It means feedback can be gathered and acted upon before it’s too late. This sends a powerful message to clients. It shows that you’re always listening and willing to act on their feedback. Compare that to the impression clients get if you only ask for feedback when the work has finished… when it’s too late to do anything about it.

NLP and modern databases provide the foundation for a holistic programme of internal and external feedback. The ability to instantly capture and make sense of any form of feedback, opens-up opportunities for real-time benchmarking.

Imagine seeing a real-time view of how your client feedback compares across practice areas, client sectors and offices. Seeing insights in context enables more agile decision-making as well as the ability to quickly identify improvement areas and internal best practices. Now imagine you can also see how you compare to the averages across similar firms. When data is instantly processed in a consistent way, decision-makers always have access to the latest client and market intelligence.

Applying AI and related cloud-based technologies to client listening, is helping firms to gain a competitive advantage. By instantly transforming unstructured data into actionable insights, AI can help firms address three significant market trends. 

They can accelerate their speed of business by keeping their finger on the pulse, improving decision-making agility, and listening to clients across all stages of the customer journey.

They can digitise their listening processes to expand their sources of client and market intelligence and then bring the real voice of the client into the heart of the business.

They can embrace outcomes-based business models by spending less time understanding client feedback and more time using the insights to drive thought leadership, new business opportunities and process improvements.