“Data is the new gold”, Michael Sinn, director of supply and category management, Otto
Humans have limits. Their expectations do not. Maybe AI is the only hope you’ve got. Beneficial intelligence report, Ubitech.
But how does one make data relevant and meaningful? What do organisations need to do and become to become and stay meaningful?
Last time – we discussed if there are not sufficient data scientists, we must invest in AI. But a colleague from kpmg demonstrated how mining existing data can produce stunning results. Using behavioural and demographic data they were able to predict student leavers, 90 days earlier, enabling appropriate intervention. See:
In addition, big data provides great insight but is meaningless if the customers’ expectations, needs and wants are not fully understood, the right questions must be asked of the data. So it is the customer journey experts who are king, not the data scientists.
For example, ThoughtWorks cite the ground breaking Domino’s Pizza – Pizza Mogul programme. It came not from the data but watching how customers engaged with the design your own pizza product. Customers were posting their designs on social media and winning followers. From this they developed the Pizza Mogul programme. Moguls create pizzas, promote them and receive a royalty for each pizza sold. Switching marketing spend to payment on results, transparent ROI and huge improvement on revenue and profit.
Key discussion points:
Artificial Intelligence (AI) – Before developing AI one needs to fill the holes in existing data but to maintain competitive advantage will need to do both in parallel.
Some roles like that of the merchandiser can be probably be better delivered by AI but never product design and customer experience design.
One has to be guided by the customer experience before the data. The trick is how intelligent you are able to get with the data.
Behavioural change – Pure-play price comparison and insurance sites are using behavioural data to suggest the next product and predict renewals. There is plenty of readily available, live social data predictive of behaviour. However, caution note, data protection is changing all the time and one may build something that is not freely available at a later date.
Online customers can become dehumanised, hosting research groups is a great way to understand their experience and group discussion allows opinions and ideas to be built upon.
Technology has to respond to changing behaviours not the other way round. In the past desk top design came first and mobile shoe horned to fit. Now it must be mobile first.
Customer insight – data and technology is available to all but it is customer insight that will inform the unique proposition, fulfilling needs, wants and desires.
The best solutions are developed from understanding the customers’ behaviours and needs. Pure-play insurance is interested in understanding how customers deal with that pile of papers sitting on the kitchen worktop. The customer experience provides insight to inform new solutions and products, the one stop-shop. This qualitative data from meeting and interviewing customers in shopping centres cannot be universalised but it provides the insight for further data mining.
Big data works but the best outcomes are when you talk to customers and understand their perspectives.
The human touch – A retailer’s brand and USP is in the hands of the staff. The human interaction brings the brand to life.
Within the logistics world all delivery drivers are remunerated the same way. One driver is more successful than another because of the interpersonal contact the customers. Feedback works, the best drivers get the most jobs. But these are the people typically described as unskilled, earning minimum wage but they have to be highly skilled in managing relationships.
Interesting that so many retailers outsource their brand to third party logistics firms when, the last and lasting experience the customer has of the retail brand, is the driver. The low cost delivery model is unsupportable but most customers (especially under 25 years) think that delivery is actually free.
Culture and retention of talent – A home delivery food business, having carved out a huge slice of the market is now losing good staff. The energising agile start-up culture is constrained by process and structure.
Retailers know their customers better than their staff, but it is the staff that deliver the brand experience. It may be prudent to invest more in staff.
A global, general merchandise, pure-play retailer has a vision of the future that is totally data driven. Not a place where people say they want to work but will happily buy from. So is this disconnect going to be an issue in the future.
Leadership and ownership – different models and owners will drive out different goals and outputs. Data can produce a long list of possibilities but the trick is to determine the right priorities and deliver. Creating the right culture for success is critical.
Digital tourism (a trip to Silicon Valley), was a great way of understanding different ways of working from start-up operations.
Within FinTech start-ups are being brought into large corporates to provide the innovation that they are unable to deliver for themselves. And there is a commune model, where complimentary providers get together to provide complete and agile solutions.
The future – The importance of customer journey and big data expertise has been made. But we are embarking on a paradigm shift, a generational shift. Gen Z (born either side of 2000) will represent 40% of consumers by 2020, have an 8 second attention span and spend 7.6 hours a day socialising. Short attention spans and umbilicaly connected to their mobiles (NY Futurologist). Do are our current customer journey experts understand the demands, wants, needs and desires of this new consumer?