Machine learning (ML) and artificial intelligence (AI) are valuable tools when it comes to developing predictive B2B ecommerce.
There’s no doubt AI was an influential subject in 2023 following the launch of ChatGPT4. However, both ML and AI have been available for a lot longer than most people think. These technologies allow us to generate valuable insights from Big Data for predictive modeling and advanced analytics.
Businesses can analyze both historical and near real time data to better understand buyer behavior. This can improve and automate marketing, increase customer engagement and improve conversion rates.
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Predictive B2B ecommerce
The Cloudfy development team embraces ML and AI and works with Azure ML services to improve B2B ecommerce functionality.
Rob Williams, CEO of Cloudfy says: “The Cloudfy technical team can optimize the use of customer order histories and broader purchasing trends to improve content and personalization. Bespoke menu features such as ‘My Regular Best Buys’ help customers find what they want easily and quickly.
As B2B ecommerce practices increasingly resemble B2C ecommerce, buyers expect high quality online experiences from manufacturers, distributors and wholesalers. We believe ML and AI help us deliver next-generation functionality that meets and beats these expectations. Predictive B2B ecommerce features are part of the Cloudfy B2B ecommerce offer.
What Is machine learning?
ML processes use algorithms to effectively learn from data and make predictions. Together with AI, ML supports services such as Apple’s Siri and Google Assistant. These tools have potential to help businesses offer more personalized services based on their customers’ behavior.
How do ML and AI apply to predictive B2B ecommerce?
ML and AI improve B2B ecommerce efficiency by streamlining data entry and minimizing manual input, but that’s just the beginning. You can also optimize customer experiences with near real time personalization and collect valuable information to help you make data-driven decisions. All your customer touchpoints and business processes can benefit from ML and AI.
A new generation of cloud based platforms is already appearing offering ML and AI capabilities such as Microsoft’s Azure ML. These help data scientists and developers build, deploy, and manage high-quality models quickly and confidently.
This allows fast and efficient development of new predictive B2B ecommerce functions and features. For example, predictive search can deliver modified search options to help buyers find what they need more quickly. They can easily search for product titles, stock keeping units (SKUs), descriptions, or article numbers. You can review their search results to add further links to other common product search terms.
Predictive ordering makes B2B purchasing easier, using previous buying histories as the starting point for new orders. It’s a more personalized and efficient experience that saves time and effort.
New features for Cloudfy are added regularly so you’ll have a best-in-breed cloud based B2B ecommerce platform. It’s built to meet the needs of a new generation of B2B buyers.
Find out more about the rich functionality of predictive B2B ecommerce with Cloudfy. Book a free demonstration today.
Frequently Asked Questions
Predictive analytics using ML and AI helps you use your sales data to improve B2B ecommerce customer experiences. You can gain valuable insights for cross-selling and up-selling opportunities and customer retention. Personalization improves too when it’s combined with data from your enterprise (ERP) and customer relationship management (CRM) systems.
By analyzing customer data, you can identify products or services that are frequently purchased together. You can also highlight purchasing patterns so you can remind customers to restock. You can tailor your marketing efforts to promote useful product bundles and anticipate production requirements to meet customer needs.
In a fast-moving B2B ecommerce market competitive and accurate pricing is important. Using ML and AI, you can align pricing with real-time market demands and customer behavior. Predictive analytics allows you to respond to changing market conditions and adjust your prices quickly. You can automate a responsive pricing strategy within limits set by you to maintain your competitive position.
Predictive analytics help you maintain optimum stock levels to improve overall efficiency whilst still meeting customer demand. Combined with data throughout your supply chain you can improve tracking, anticipate disruptions and price fluctuations to improve your planning.
