Would you like fries with that? Automating upselling

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Upselling is an unpleasant part of any salesperson’s job, for the large part, requiring bare-faced attempts to get customers to part with yet more of their - or their company’s - cash in search of recognition or, even better, commission.

For this blog’s author, the nadir came when selling warranties on gaming consoles for a popular high street electronics store. Charging punters £20 a go for a paper-thin insurance policy on a pre-owned X Box did not feel so good.

Luckily for me - and for sales staff everywhere - Oracle has come up with a cloud-based solution to save embarrassment all around.

Customer recommendations

The computing giant’s “Hospitality Menu Recommendations Cloud Service” is a brand new addition to a suite of products that fall under the banner of “Data Science Cloud Services” that are available to Oracle’s corporate customers. The recommendations service is designed to let hospitality organisations automate the process of finding up-sell and cross-selling opportunities on new sales.

These recommendations are delivered based on location, time or day, with further dynamic updates given depending on customer behaviour. The assumptions made by Oracle’s service are then available for further analysis, leading to a better understanding of customer behaviour and preferences.

Which means that we could envisage a future where the till -rather than its operator - will be making suggestions of add-ons to customers.

The applications outlined by Oracle remain pretty rudimentary: use cases paint the reccomendations service as a replacement for the perennial “would you like fries with that?” question at fast food joints, or asking restaurant-goers if they would like a paired set of wines with their meal, or if you need that X Box insurance after all.

Virtual advantages

The attraction of this software for business owners is easy to see. Not only does Oracle’s Forecasts platform promise to use this customer cross-selling data to help better predict stock and labor needs at locations, it can also provide real-time access to key performance indicators (KPIs) to constantly grade your sales staff’s performance.

“Such forecasting maintains appropriate levels of inventory and staffing in all business scenarios, helping store managers minimize wasted inventory, lower labor costs and, most importantly, ensure an exceptional guest experience,” continues the firm’s press release.

Indeed, labor and inventory costs were estimated to eat up more than 50 per cent of US restaurant revenues, according to a survey of more than 200 independent operators and chains conducted by Oracle.

But how desirable, or even useful, is automated cross-selling to a customer base likely already sick of intrusive web adverts?

Well, one obvious answer is that customers would prefer getting what they like from the shops or restaurants they frequent. Though in many instances the removal of a human recommendation might be a negative factor but, as shown through McDonald’s early success with self-order kiosks in the UK, customers can often find it more palatable to be asked such questions by a machine.

That means more satisfaction for customers who find what they need, and better sales for companies that may have struggled to find the right add-on for a given customer. It might also mean shorter queues in locations, reduced staff training costs and other, unforeseen advantages.

As Richard Goodall, vice president for hospitality at NCR notes, “consumers want the ability to purchase in the most convenient and simple way for them at any particular given time”.

Potential for misuse

Having such data available for view in real-time is another crucial advantage for retailers.

Kevin Greene, international product manager for CBE Software, said the real-time element is a “key benefit” of using an all-encompassing, cloud-based system such as Oracle’s.

Greene also warns, however, that there is potential for the technology to be misused, both to overly-aggressively sell product to customers, and to potentially alienate human staff and lose their trust.  He suggests that, for example, restaurants use their real time data to reward staff and front-of-house team members who are performing particularly well, rather than relying on the virtual prompts completely.

He adds: “With the technology continuing to evolve at such a significant pace, suppliers need to stay ahead of the curve by regularly developing their offerings to deliver a holistic, smart solutions for restaurant operators.”

So, it might not be long before we never hear the beautiful phrase “would you like fries with that?” from a human mouth ever again.





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