Everyone who has purchased goods from Amazon has seen the “related to items you’ve viewed” or the “inspired by your shopping trends” or the “recommended for you in kindle books” sections. These sections of product recommendations are always spot on, and, if you’re like most people, it is very easy to click on. That is because they are drawn directly from your past purchase history and what you have most recently viewed on the website.
Amazon has been providing ever improving recommendations for years. This comes as the result of increasingly proficient machine learning technology. From the data Amazon collects on the activity of customers like you, they are able to leverage machine learning technology to provide eerily accurate predictions and recommendations on products that you will be most likely to purchase.
While Amazon’s case study has unconditionally proved the benefit of a machine learning powered B2C ecommerce platform, can this same technology be applied to B2B ecommerce platforms?
Building a Successful Ecommerce Platform
To see how machine learning can be applied successfully to a B2B ecommerce platform, one must understand how to build a successful platform in the first place. Below are three best practices toward building an effective platform in the modern business environment.
Solutions in the cloud
Historically, B2B ecommerce projects have been exceedingly expensive and slow to develop – with roll-out taking up to 2 years in some cases. With the speed at which businesses move today, you can’t expect such solutions to provide real value. It is essential for B2B ecommerce platforms to be hosted in the cloud – allowing for deployments of a single business quarter.
Agility is a Must
By enabling a company to call upon a SaaS solution, they can deliver initial capability while allowing the solution to evolve over time and shift with changing needs. Companies can initially focus on the most impactful use cases, delivery immediate return.
Ecommerce Solutions Must Be Omnichannel
While some platforms are extensions of ERP systems and others extensions of CRM systems, a true omnichannel approach can interact through the same platform, enabling a single view of the customer.
Bringing Machine Learning into the Fold
To answer the question in the introduction: yes, companies today can, and need, to implement machine learning in order to have a smarter, more efficient B2B E-Commerce platform. Like in the Amazon case above, many B2B companies have been collecting incredible amounts of data throughout the past decade. The difference, however, is that many of these companies are relying on simple descriptive analytics to derive value. This is simply not enough to produce the business outcomes that many companies require.
Bringing machine learning into an ecommerce solution allows companies to more effectively leverage their stores of data. By incorporating the technology, you can present customers with ever-improving and relevant product recommendations, services and dynamic bundles. You give yourself the ability to intelligently identify the exact pricing triggers that bring your customers back, and speed up sales cycles through the use of intelligent and dynamic promotions. Machine Learning Intelligence gives all types of companies the ability to offer the right products at the right time.
In today’s competitive business landscape, it is essential for companies to leverage modern technology to drive the outcomes they require. Machine Learning is one of those technologies. Its use cases are evident and validated, and it can be applied in any business – including B2B business – to drive ecommerce success.
Maria Pergolino is SVP of Global Marketing & Sales Development for Apttus