Irina Lam [OmniConvert]: Digital Sales in the Artificial Intelligence Era
During a phone call, you can gain or lose a client. Regardless of whether you answer the phone in the office or the store, you should focus on providing high-quality customer service.
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One of the speakers was Irina Lam, Head of Business Development at OmniConvert, who said a few words about digital fields in the artificial intelligence area. We’ll dive deeper into how our jobs and tasks are going to be affected by AI by 2020.
„A couple of months ago I attended a marketing conference in Berlin and was confused walking through the aisles of thousands of exhibitors. But something caught my attention as I was passing by a big TV screen. I noticed it was video recording the people passing by.
The gadget is a digital screen that wraps around retailers chills and displays digital Ad that can be swapped out the fly. The technology can examine someones facial expressions and let retailer set traffic patterns and are gender, demographics, and even real region to some extent. And this is just what’s happening in the offline”.
Nine years later, Amazon was taking over flying retailers. We’re currently spending on almost two trillion dollars in sales for worldwide e-commerce combined. And by 2020 this number will reach for trillion.
How about AI and robots taking over our jobs in the future? What’s the marketers or sales manager struggle? Of course, connecting the right people to the right products at the time and generate sales now. How do we do that? We track, we understand and adapt.
When tracking users product, product feedback, purchase in our Google Analytics for assurance and then we’re trying to compile the data in our minds and figure out insights on the low-hanging fruits and their motivations while at the same time we’re trying to come up with ideas to change and implements where that thing offers as the content.
What we do as digital marketers? We manually look at the first second, trying to find patterns, aggregate data and take action on clusters based on online average order value for a person or a team. Only to be able to look at millions or trillions of entries and figure out solutions for their email marketing strategy or output. Website personalization based on huge amounts of messy and all over the place data is close to impossible.
Our intelligence has a very poor understating of what intelligence is. We think of it as agile dimension take a cube, for example. So we got average people , star and dump people. What artificial intelligence douse is a connection of the different intelligence clusters and creating the machinery which has the vegetable world.
5 machine learning features that will be heavily adopted by 2020:
1) Customer service chatbots.
It is no secret that in this instant gratification economy customers demand immediate responsiveness from brands and expect fast and reliable customers service then that’s a cross-world channel. Chatbots are replacing live chat another form the slower communication such as phone calls or emails. Chatbots provide immediate customer service that offers concise answers to some of the most frequently asked questions.
2) Dynamic pricing.
Another thing that I want to talk about dynamic pricing. Dynamic pricing based on machine learning and is a pretty recent innovation. Dynamic pricing is a powerful alternative to segment pricing. It automatically optimizes prices for every user in real time without the need to manually define or text conscious pricing rules.
3) Product recommendations.
YouTube is currently using one of the efficient recommendation engines in the industry. With using the Google brain system one can experiment with different deep neural network architectures using distributes training.
4) Better customer segmentation.
I can’t stress enough on the inefficiency of creating clusters manually by combining different segmentation points to define patterns and then finally finding out what works best for each cluster.
5) Improve Product Search.
We all know that search is the key in online sales. Visitors using the search bar are, for example, five times more likely to convert than the ones who don’t. Machine learning algorithms will vastly improve e-commerce product search capabilities. Improved learning search will consider any quick rate, conversion rate, customer reading, and even product inventory or margin. These learning search system will deliver product results that your shoppers are more likely to buy.
A few weeks ago I ran on the Guardian a declaration of the founder of Alibaba. He said that leaders who don’t understand that cloud computing and artificial intelligence are essential for business, should identify young people in their companies to explain it to them, and maybe that’s one of the reasons I’m here speaking.”
But leaving jokes aside, I believe, and that’s my personal opinion, that the future of marketers and salespeople comes down to how quickly we are able to adapt and understand that old ways are getting really old very soon and will no longer bring us the results we need to beat our competition. I think it will be the early adopting businesses which will thrive in the next few years.”
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