You’ve completed your detailed customer journey maps and utilised AI to automate and analyse user journeys for a newly launched service within your existing portfolio. But somehow, there is less traction than you had imagined. Customers are unhappy, and potential customers aren’t convinced.

“What might be missing?” you might ask.

In an age that’s super-charged with data, we have the ability to track almost every single movement, interaction and touchpoint of our customers. There is sometimes a desperation of wanting our customers to do what we want them to do <what’s good for our business> and eventually say yes to us<buy, purchase, subscribe>.

But are we really finding the signal in the noise?

Out of habit and convenience, are we increasingly categorising people like items on a shelf? With an increase in hyper-personalisation fuelled by AI capabilities, might we be adding more items and more shelves to replace the humans who are our customers?

“Our plan is to send a survey to 1,000 people instead of spending an hour each speaking to 10-15 real customers. That way we save time, resources and budget while still getting similar results! So why spend time speaking with customers? There’s no time for that.”

These are some of the remarks or questions that I encounter while facilitating workshops on Design Thinking or Jobs To Be Done. According to McKinsey, “Customer surveys, which have long served a foundational role in data collection, are waning in effectiveness as response rates decline.” This trend highlights the growing need invest more time in uncovering the progress that individuals are trying to make in their lives.

There is a fine balance that needs to be struck between the magic of AI and the wonder of human centred innovation. According to Forbes, if the balance is tilted too far towards AI, organisations may end up losing customers. “As companies strive for efficiency in support, have they inadvertently made the customer experience worse? Spending on AI and automation would be justified if it actually solved issues more quickly and boosted customer satisfaction. Instead, the data suggests the move toward AI is actively repelling consumers.”

Also Read: 3 ways AI technology can help startups save money

What if the script was flipped and the control of AI was given to customers instead? In the case of IKEA, they are “unleashing the power of generative AI to give customers even more power when it comes to designing their ideal homes.” However, a purpose that lies at the heart of their innovation process is “the need to prioritise human values, asking if actions respect human agency and dignity and if a people-focused approach is central to all initiatives.” This is part of their digital ethics policy that was launched in 2023.

Investing time in honing the craft of unpacking qualitative insights overlaid with quantitative data would help us better understand what customers want to achieve and how they might go about achieving it. This is when job maps and customer journey maps might help to bridge the divide between human needs and technology driven journeys. I have created a free template in Miro can help your team begin the journey of bridging the gap between the how and what.

Customer journey maps and job maps

A customer journey map is a fantastic way to show us what customers do. While it provides huge value to organisations, it leaves a blind spot on why customers do what they are doing. This is where job maps can take us further into the journey of finding the signal within the noise.

According to Jim Kalbach, a job map is not a customer journey map. “The aim is not to document how people come to your solution, decide to purchase and stay loyal.” That’s not their job to be done. Instead, a job map is a view into the behaviours and needs of individuals in the context of their daily lives. That may or may not include your solution.” (Kalbach, The Jobs To Be Done Playbook, 2020).

But why should one bother if it may not include my solution? This is where combining the what — a job map — with the how — a customer journey map — could help create a more comprehensive view of your customer’s entire journey within the context of their lives.

Job maps help us navigate from why to where to, giving us the ability to view the entire picture through the lens of a customer. Investing time in understanding their hopes, fears and what progress means in their lives, we will be able to unlock avenues of innovation at multiple levels.

Also Read: How should non-tech companies approach AI?

Steps to consider

Recognise the lure and limitations of relying on or prioritising purely quantitative data analysis, such as surveys.
Invest in spending time with your customers to uncover their motivations and underserved needs.
Create job hierarchies to uncover pockets of innovation at each level.
Develop job maps to keep your customer’s needs at the heart of your business.
Use AI as a co-pilot, not just for prediction (highly risky) or completing tasks.

In the never-ending quest for being truly customer centric and trying not to “centricity-wash” an organisation, having a shared language around needs and motivations helps to guide businesses closer towards their North Star Metric.

Organisations that are able to balance the patient craft of uncovering undermet needs and prioritising based on where underserved opportunities lie, while simultaneously accelerating outcome-driven-innovation and adopting new ways of working with AI, may find themselves more relevant to evolving audiences.

As we navigate this brave new world, let us not forget the fundamental truth that has always underpinned successful business: at the heart of every transaction is a human need waiting to be met. In understanding and serving that need lies the true path to innovation and growth.

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