Artificial intelligence (AI) is one of the greatest hypes of recent times. AI has a wide range of applications for retail. There are already some outstanding examples today of how the new technologies can be put to concrete use in retail.
But where within a company does the introduction of artificial intelligence pay off most? A study by the market research company Gartner examined the contribution of AI to the value of a company. The conclusion: In the coming years, improved customer experience in particular will ensure that artificial intelligence becomes an increasingly important business factor. In today’s third part of our series “Retail in Transition”, you will discover how an improved customer experience can be achieved with the use of new technologies.
Excellent customer relations: Those who know their customers particularly well get the business
Successful retailers know their customers. This may seem to be given, but it isn’t easy to implement. In brick and mortar retailing, you may recognize your regular customers personally and be able to advise them individually. But does every employee know them as well as you do? Artificial intelligence is not just a tool that can be used for e-commerce to reinforce customer loyalty and increase the individual buying experience; it goes beyond that.
Customer satisfaction is a valuable asset. According to a study by management consultant Forrester, 80 percent of American companies surveyed feel that buyers increasingly expect to receive relevant information when purchasing. Almost 80 percent of those surveyed also describe that their customers are more impatient than ever before. This is why their first contact must be a good one. If it isn’t, potential buyers will quickly withdraw from a purchase.
So how can you increase customer satisfaction in the future? According to Forbes, the use of artificial intelligence is a promising solution. 75 percent of companies that use AI increase their customer satisfaction by more than 10 percent.
How customer relationships are captured digitally
A successful relationship with customers in online retail is based on large amounts of data. In customer analysis, for example, biographical information such the customer’s age and gender or their status (new or existing customer) is available. Other data on the sales environment is also normally available, such as the buyer’s geographical IP address or the type of device used to access the website. In addition, data such as the amount in the shopping cart and product categories offer further clues to better assess the customer.
Information such as how long your customer stays on certain product pages, or reviews and news that your customer provides about your products, also provides additional data about their shopping experience.
Deep retail: using new methods to strengthen customer relationships
However, unstructured data is useless if it is not consistently ordered and evaluated. This is where artificial intelligence comes into play: the algorithms are programmed for specific tasks and over time constantly improve the way problems are solved. These algorithms are therefore ideally suited for those areas of customer management that already today no longer require human service.
There is gold to be found in the data available. The modest goal of deep retail is to know your customers better than they know themselves. These three technologies are particularly worth adopting in order to offer your customers an individually pleasant shopping experience:
Use chatbots to maintain fast and direct customer contact
Chatbots are artificial intelligences that function as personal assistants. They can be contacted via the chat function on the company website, in your own app and in external apps such as WhatsApp or Facebook. A chatbot is available around the clock to answer questions or provide advice. Using a self-learning algorithm, it is always learning and improving its interactions with customers. The advantages are obvious: According to Springer Professional, chatbots can measurably shorten the time taken to process complaints and improve call volume processing. Even today, 25 to 50 percent of all inquiries can be answered completely via automated channels.
Do customers like your service? Sentiment analyses shed light on these issues
Sentiment analysis is a method of obtaining information primarily through text mining. Artificial intelligence uses statistical and linguistic methods to search through all the sentiments that customers digitally record for your company. Complaint forms, product or service reviews, forum postings and social media articles related to your company are all consulted.
What may seem simple at first glance can be quite complex: The example tweet is obviously a negative sarcastic remark about the service of a café. Nevertheless, the positive words “wow” and “great” are used. This is where artificial intelligence has to be programmed well enough to understand the context of the rating, rather than just using the words used to mark the tweet as a positive utterance. In addition to textual information, visual and auditory content is increasingly being used for sentiment analysis. Videos, photos and podcasts, for example, are evaluated for this purpose. Through the analyses, you learn where customers rate your service positively and where they see an urgent need for improvement. Sentiment analyses provide you with the opportunity to identify your own strengths and consistently improve in your customer relationships.
High customer satisfaction has an impact on price perception
When it comes to achieving the closest possible customer relationship, price perception is more important than the price itself. Pricing should therefore be based on the customer. The stronger the customer loyalty, the more likely the customer is to accept higher prices. Because: Customers never just evaluate the price, but always use an individual price-performance ratio as a yardstick. How valuable is the product to me? What do I think of the supplier? What other vendors are there for the same product? Market analysis tools such as blackbee Insights are ideal when it comes to keeping an eye on competitors. Insights mainly processes textual information for the analysis of competitors and price developments in the market. In the future, image processing will also be added, and the price and market analysis will be raised to a new level.
Would you like to learn more about the innovative solutions that our market analysis tool blackbee Insights has in store for you? Our pricing experts will be happy to advise you personally.