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Chatbots in Retailing – a Fact or a Fad?

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Retailers are frequently yelled at by frustrated customers, or, if things go well, they are commended. That’s part of the emotional exchange that comes with a retailer’s job description. However, chatbots may change all of that.

A chatbot is a computer program which conducts a conversation via auditory or textual methods. In other words, sales assistants in a number of retail businesses are now robots. To this end, bots can help retailers in many other ways.

“Chabots are seen as easy and fun ways to help customers achieve an outcome. You’ll encounter them on web sites, social media and even on your smartphone. Say hello to Siri, Allo and Alexa, to name a few”, writes Christine Crandell recently in Forbes.

Siri, Allo and Alexa are computer characters which, through natural language-style dialogs with humans, perform various tasks, such as answering questions, helping them to navigate websites. “They can either look like a human being, or a digital avatar, an animal, alien or may have an image that does not look like a living creature at all” according to ChatBots.org

Apart from retailers not having to face angry customers anymore, the bots allow Bricks and Clicks retailers to catch up on lost sleep. A chatbot is a handy aid for retailers with online customers when their bed time arrives.  “We’d all like to be all things to all customers, but even the most dogged marketer has to sleep sometime”, according to TargetMarketing magazine. The fiction of chatbots has now became a reality as many retailers has bought into the technology.

How chatbots can be used by retailers

Chatbots can be used in many ways by retailers. Nicki Baird (Forbes) suggests that chatbots can do everything – from interacting with customers about new products, to helping them to figure out the trading hours of your shop. Furthermore, leverage chatbots the ubiquity of messaging apps and allows retailers to conduct one-to-one conversations with customers in real-time. Besides, retailers have the opportunity to make money with chatbots.

Ross Simmonds (Crate, Hustle and Grind), identified seven ways retailers can make money with bots:

  1. Bots as a Services (BaaS) – help people and teams to be more productive. They can manage tasks or tackle communications challenges – by replicating business models already in use;
  2. Bots plus sponsored and native content – native or sponsored content is a model in which brands pay to have their content distributed by media companies directly into their channels;
  3. Bot leveraged affiliate marketing – for example: retailers can develop a bot that offers tips and tricks on how to stay healthy and use affiliate links to send people to fitness products that have affiliate links associated with them;
  4. Bots for research – there are bots that you can pay to do the research for you.
  5. Bots for lead generation – may act as a lead generator with an initial focus on content. Chatbots designed to deliver insights and information to users who are looking for advice or information can be lined up with products that the retailer offers;
  6. Pure retail sales bots – the user will make the purchase directly through a chat with the bot and it will act similar to a transaction from a typical website;
  7. Cost per conversation/task – as bots become more sophisticated, people may be willing to pay to have conversations with the bots that can help them with various challenges in life.

“Thanks to big data, artificial intelligence (AI) and predictive analytics, as well as the proliferation of messaging apps, retailers finally have the tools (including chatbots) to get the right messages to their customers”, suggests Craig Alberino in TotalRetail. However, the chatbot hype is not favored by everyone…

Consumers that use  chatbots can complete a purchase in a minute or two. Have a look at the video from Kore:

The future use of chatbots

Although the use of chatbots is getting much attention nowadays, not everyone is excited about it. Jon Evens writing last year in The Walrus reminded us of the “Eliza effect: “Humans unconsciously assume that software which communicates conversationally has much more intelligence and sophistication than is actually present.

Inevitably, the software eventually fails to match that assumption, disappointing and frustrating the user who unconsciously expected more.” Consequently, your frustrated customers may want to communicate (again) in person with you. Because the computer does not understands… Above all, what is good and bad about chatbots? Quora.com responded as follows:

The Good Things About ChatbotsThe Bad Things About Chatbots
1. Chatbots are a good alternative for mobile apps1. Chatbots have a high error rate
2. With bots, nothing new needs to be learnt2. Chatbots don’t put people first
3. Bots are capable of providing a great user experience3. Bots are limited in their capabilities
4. Chatbots as the factotum for all business needs4. Chatbots aren’t as intelligent as humans

Concluding

In summary, are chatbots the “silver bullets” that retailers can use to compete in a digitized retail environment? Or will it be another fad with demanding customers not getting assisted properly? I suppose we have to wait and see. However, Leo Sun (fool.com) recently asked: “Were the social network’s chatbot ambitions ahead of their time?”

Importantly, this is after Facebook is reportedly scaling back its chatbot efforts on Messenger after the programs failed to fulfill 70% of users’ requests. Consequently those requests couldn’t be handled without human agents, and bots built by outside developers “had issues” because the “technology to understand human requests wasn’t developed enough.”

Finally, perhaps Dale 1, (2016) sobering comment can be noted by all: “If we want to have better conversations with machines, we stand to benefit from having better conversations among ourselves.”

A Marketing Plan helps you to communicate the right content to the right audience.

Additional reading:

  1. Artificial Intelligence – Digital Outcomes or Digital Disruptions for Retailers?

Note:

1 Dale, R. 2016. The return of the chatbots. Natural Language Engineering, 22(5):811-817.

Image and video:

  1. Pixabay
  2. Kore

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