Asked for predictions and future trends, younger people and elders forecast a different future. The judgement is based on past experiences, where the elders had a longer time to watch. Now there is research which uses stock market predictions and inflation expectation to measure the difference in estimation between age group.
Ulrike Malmendier and Jessica Wachter show in their paper how long time experience correlates with investment decisions. People with long experience include old information in their judgments. Do they make better predictions? The study has no answer for that.
Past experiences stick. Did you ever notice the warm emotions showing up when memories to a nice situation long ago appear? Another nice thing of the past is that we know how all ended. And we can connect with others about the long gone events.
For the ones who follow politcs: party members choosing a candidate are mostly elder and more extreme than the ones who vote. So their candidate might have problems.
Artificial Intelligence has no memory
Humans differ from artificial intelligence in learning. AI connects the data and learns from what was in short sight. Humans take their whole life experience together and build their judgements on that.
Hiding the past helps sometimes
There is a connection between memories memories in market research and in own, personal ways to think and judge. Discovering the role of memories in own judgements and being able to switch it on and off helps to get a better picture of the world of younger people. It is about trying to look at the world while leaving out past memories.
Having a long memory may be helpful in forecasts and judgements. Mathematical evidence from the stock market does not give any proof for that.
Customer journey and past experiences in market research
Along a customer journey the traveller takes a lot of decisions. Will old memories take a big influence on that decision? Research shows it does. Big example are cars. Seniors buy different and bigger cars.
The article deals with the possible uses of automated product recommendations in sales and customer service. There are buyers who prefer to buy on the internet for there they do not have to talk to human sales representatives. They probably had some experience with vendors staff hiding their cluelessness behind a lot of talk and are trying to sell their products on stockage at anyone who does not get away fast enough.
The problem looks hard to solve. But wait: for a few years now it is possible to extract valuable data points from primarely web activities and connect them with realised sales. The connector are either self-learning models or static traditional models. Models simulate behaviour and results.
The interested customer is looking für information before buying. He or she may ask a specialised salesperson and consultant who has all the relevant answers ready and can think in the customer’s interest. This relieves the customer. Or they, the potential clients, may look for publicly available information and customer review to avoid the advice of an inexperienced and overburdened sales representative.
Many sales representatives for complex products are quickly overwhelmed by the questions and expectations of well-informed prospects. The untrained salesperson feels attacked, the sales talk goes off the rails, the interested party prefers to buy from a supplier without advice.
The web part of customer journey
Depending on the product, between 80% and 90% of the buyers begin their customer journey with an search engine. So it is important for the seller to know what it is reported in the web, take care of the correctness of web information and avoid contradicting information. If there is human sales staff, they are supposed to assist the web customer journey and take care of a seamless process.
The consultant with all the facts in mind and the fully automatic customer advisor are extremes, the practical truth in the company lies in between.
Can the web be the better customer advisor?
Yes and no. The informations in the web and the informations given by a human sales person are supposed to go without contradiction. Nobody likes lies and deception.
Artificial intelligence makes use records of any communication with customers, for example chats, mail, data entries. This is compared with predetermined success goals. The model recommends something and can adjust itself. Something salespeople do intuitively, too, if the selling company lets them. Artificial intelligence therefore means less control for the management. On the other hand, opportunities are used that might otherwise have been overlooked. Where to start now?
Sellers are supposed to make as much information as possible available in a neatly structured way. Many people would like to find out more before making personal contact, but cannot find the information they are looking for. If publicly available documentations saves half an hour of calls per working day for the seller this justifies an expense of €2,000 for an improved sales website or other type of customer information – and that for telephone staff at a standard wage. Informed customers are better customers.
The meaning of human interaction
The ideal salesperson knows the buyers needs and wishes. He ors she build the best possible solution with his expertise. In between, looking up details and availability on the computer is essential for complex inquiries.
Advice form humans or from machines and websites?
Whether or not a human intermediary remains necessary for information collection and transmission depends on the product itself and on the personal preferences of the interested party. Some can evaluate and implement the freely available information, such as product descriptions, customer reviews and more for their own needs, while others cannot.
Good sales people relieve the customers. To do this, they must put the interests of the customer first and not fight for sales at any price. Consulting software in the sales pitch gives standardized information, if the software is capable of extracting the recommendation which work and then the client might be really happy.
Success has many reasons
Incidentally, the screen of the gentleman can turn directly to a prospective customer without the computer interfering. And if he needs information from the cloud or machine, he has it quickly at hand.