Artificial Intelligence (AI) powered eCommerce store

Undoubtedly, Amazon is considered to be c-suite of every brand.

Be it their usability, recommendations, or membership perks, Amazon, the 800-pound gorilla wins over others because of its perfect customer service on a big scale.

Size does not matter here! Amazon business size has nothing to do with the success of their customer service. Many businesses do not realize this.

Particularly in the AI front, one can expect even more innovative concepts forthcoming from Amazon.

Why?

This is because; the patent on one-click payments of Amazon is set to expire soon.

Nevertheless, this will not make any major dent to Amazon as it will not feel the pinch. The giant will still be dominating. On the contrary, it will find new ways aggressively to be prominent and tower above others.

As a routine and as part of its development program, Amazon is filing numerous machine learning and AI-focused patents.

Personalized online experiences powered by artificial intelligence will be the expectation, very soon.

The Future of AI, Retail and ROI

Eventually, AI enables an E-Commerce website to recommend products suited to shoppers and enables people to search for products, unique in nature, by virtually using conversational language or images, as though they were interacting with a person.

This has been one of the key missing requirements for a larger E-Commerce revenue share within the retail industry in a bid to beat the traditional brick-and-mortar stores that offer personalization.

By the same token, other evolving opportunities include using AI to personalize the customer experience through their online shopping journey.

Primarily, this could be a great value-added service to online retailers.

By a report by Boston Consulting Group (BCG), retailers that have implemented personalization strategies see sales gains of over 6-10%. This increase is two to three times faster than other retailers.

According to Accenture, by 2035, it could also boost profitability rates by 59% in the wholesale and retail industries; which could be a possibility, though this appears surreal and far-fetched at present.

Think of it, with AI, there are many opportunities and prospects, but what does it all mean? Moreover, where does one begin? Top of Form or Bottom of Form.

The AI Expertise Gap and How to Solve It

Many E-Commerce leaders are trying to assess and evaluate how data and artificial intelligence can be their differentiator.

Some trending patterns have emerged on where the industry is focused as far as retailing is concerned.

Barring a few companies who are actually executing their AI initiatives, others get stuck on how to start, which is not an encouraging indication by any standards.

Considering the fact, that there are common barriers to start an E-Commerce AI, an initiative has to be taken to overcome those barriers.

Lack of Orientation

Lack of vision, clear strategy and positive focus are the principal reason why companies have not piloted projects for AI.

It is very vital to stay oriented by having a clear vision of how AI should be put to optimal use to drive E-Commerce and how to execute.

It would be appropriate for the companies to assess their data and understand where their data provides differentiation or variations.

Once the value within your data is determined, the next step would be to have AI understand relationships better between data sets and also predict what will happen next, and/or automate processes, etc. in that order.

Therefore, it is wise to have a roadmap for both near-term and far-reaching implementations for the success of a business.

Expertise gaps.

It has been found that many companies just do not have the requisite set of skill to get started, even with initial hiccups. But all AI projects require data, machine learning, and technology experts working together in tandem to initiate the project.

Generally, companies struggle maximizing on data projects as they lack correct expertise on a particular project. At any given time, expertise is in high demand and this trend will always remain that way.

Bad Data.

Bad data is not good, leave it to AI. Artificial Intelligence output is only as great as its input, which is a known fact.

You tend to limit the AI abilities and its values if you don’t have the right quality or quantity of data.

Although many companies are committed to collect and store data consistently for their business, yet they lack the right resources and understanding to identify the good from the bad.

The most valuable data for AI remains hidden in flat or unstructured files.

Competing Technology Priorities.

Evidently, many companies are often unsure, rather unaware of how to pile up rank AI spends against other technology and information spending.

Quite often the CIO and CTO need to align and pool budgets to execute successful projects for the business. For which data is captured, stored, accessed and processed regularly.

Unclear use-cases

Next to “lacks a clear vision” the top barrier to AI adoption is the uncertainty around finding relevant use cases.

It is important to understand what is easy and what is difficult in artificial intelligence currently for online retailers like you or any business house.

Therefore it is critical to move away from a passive state of AI exploration to an active state of piloting projects.

To close the thinking-doing gap:

– Take a pragmatic and sensible approach.

– Identify narrow use cases that are well-supported with data.

– Choose open-source AI algorithms or companies offering SaaS products to instantly taste success on small projects.

– Learn what an AI win looks like and the process involved in creating them.

The Knowing-Doing Gap has to be confronted with the challenge of turning knowledge about how to improve performance into actions that could produce measurable results.

Let us take the lead and get started.

The Economic Benefits to E-Commerce AI

Those who have evolved from thinking to doing are now appreciating the benefits.

Top benefits of AI in E-Commerce are:

– Enhancing product development.

– Making better decisions.

– Announcing the creation/launch of new products.

– Optimizing processes.

– Regularly, identifying new markets.

– Automating workflows.

These improvements eventually help with automation and saving time.  Besides, it is instrumental in generating faster revenue. Thanks to better decisions and a clearer path to success.

Length of Time to AI Implementation ROI

What is the lead time to actually realize the ROI on an AI implementation?

Usually, one tastes success immediately after initial pilot projects, but many companies have agreed that they gained substantial benefit after launching several projects.

So, the more you try the more institutional knowledge you create for your betterment.

Quite a number of companies are taking a Lean Startup approach and rapidly deploying projects to test and learn to improve their business. Retailers who are taking action are making their intentions known.

Until recently, many of the enduring brands have announced their AI projects on their earnings calls.

Contrarily, it has been found that companies that have failed to adapt to customer and technology trends are shutting down operations, which is not a good trend. Go to see, AI is both exciting and scary.

The opportunities to serve customers better and understand their demands in order to offer better products or experiences with less guesswork should strengthen all businesses.

However, one is apprehensive even to think about all the accelerated benefits derived from the intelligence and capability awarded to first-movers compared to the wait-and-see crowd.

Mind you, the key to getting started is well known; that which use cases to deploy, have a solid strategy and pilot small projects for incremental ROI.

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