How AI is Transforming & Shaping E-commerce Models

For certain industries, the emergence of the internet drove nails into the coffin of traditional brick-and-mortar retail. Now AI is set to do much the same thing for many of the processes in the now-standard e-commerce models.

Supported by ever-improving cloud resource distribution and IoT technology, here are some of the major ways in which AI is overhauling the basic structure of e-commerce models and forcing retailers big and small to move with the times or be left behind:


This entry is a guest post by Patrick Foster, a writer and e-commerce expert from Ecommerce Tips — an industry-leading e-commerce blog that shares the latest insights from the sector, spanning everything from business growth hacks to product development. Check out their latest posts on Twitter @myecommercetips.


The Internet of Things (IoT) is automating purchases

Bulk buys are common in certain industries. And instead of assigning these buys to be done manually by individuals, or carried out at set intervals regardless of the rate of use, IoT technology in the form of inventory management and ordering software can be left to handle them.

e-commerce models

For example, an internet-connected smart fridge can automatically place fresh orders for certain items when they reach set thresholds. The user will be able to ensure that supplies are replenished at the ideal time. This cuts down on admin time and saves costs that result from excessive or insufficient resupplying.

Retailers can support this action by bringing their e-commerce models to the 21st century. Brick & mortar stores should make their systems easy to access through IoT technology-driven devices and offer suitable purchasing and delivery options.

Programmatic advertising is fine-tuning PPC

PPC was originally about configuring ads and budgets, then choosing where and how often to display the ads. Programming advertising is much more nuanced.

The programmatic marketing industry relies on sophisticated networks of PPC algorithms that collate available user and session data and use the information to choose, wholly on-the-fly, which ads to display when a page loads.

This grants the ad-buyer a much greater degree of targeting. First, they can specify a particular age demographic. Then the algorithm sets the ad to display only when the user falls within that demographic. If a user loads a page with supported ad space but isn’t the right age, the programmatic algorithm won’t select that ad. 

In the future of IoT technology, this process is going to get even smarter, and even more of the paid marketing industry will be about setting parameters and letting AI decide the specifics of running ads.

NLP is advancing voice and search options

Comprehensive Natural Language Processing (NLP) has long been a primary goal of the AI industry, and in recent years it has made huge leaps ahead to become genuinely viable in many real-world situations.

Without solid NLP, Apple’s Siri assistant would not have been possible. Nor would have Google’s equivalent assistant or Amazon’s influential Alexa platform. Through being able to parse voice and typed search inputs and glean user intent, they can provide information, answer questions, and take actions on behalf of their users.

Natural Language Processing Web

Natural language processing is an area of computer science and artificial intelligence concerned with

the interactions between computers and human languages

This is big for e-commerce models because it reduces the amount of work that goes into placing an order. This is a giant factor in increasing conversion rates. When someone wakes up in the middle of the night craving a particular snack, they’re unlikely to boot up a laptop and place an order. Although, if they have an Alexa-type system at hand, they may well succumb to temptation and place an order before going back to sleep.

The convenience also extends to the oversight and organization of the stores themselves. In 2016, Shopify notably acquired Kit CRM (a virtual assistant) to provide expanded control options, allowing those who use its DIY e-commerce site creator to set sales, run advertising and make various admin changes through a natural language messenger-based text interface.

E-commerce retailers that don’t want to be left out must ensure their content is accessible to NLP technology. If systems can’t interpret their copy, they won’t appear in results, and if their store setups use awkward APIs. This results in a hard time controlling them remotely.

AI Chatbots are driving conversions 24/7

Gone are the days of needing to wait for the 9-to-5 period to speak to an assistant. Not just because remote assistants have made it easier for businesses to have round-the-clock support services. Instead, it’s because AI chatbots are automating many of the most basic support tasks, and by doing so, converting the sales process to always-on.

For example, a user can visit an e-commerce site and ask a chatbot if an item is in stock. It will tell them immediately, then provide them with relevant buying options. Whoever configures the chatbot can define its responses and give it escalation options. These options include things like offering discounts or granting free next-day shipping.

AI Chatbots

If you’ve been to an e-commerce site lately, its likely you’ve experienced one of these chatbots!

AI chatbots aren’t currently all that smart, but they’re getting better at a fast pace, and options are multiplying. Sooner or later instead of training e-commerce sales staff, companies will be able to set up advanced AI chatbots that can identify the best possible sales pitches for any given scenario.

Retailers that want to make the most of this should start codifying their customer support processes. This identifies the most common issues and opportunities. The data can now fold into an AI chatbots system at an appropriate time.

 

The new standard for e-commerce models

If you’re in the e-commerce industry, you should be giving AI and IoT technology some serious thought. At some point in the near future, you won’t be able to avoid using it. The faster you get up to speed, the quicker you’ll be able to take advantage and implement it within your own e-commerce models.

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