Author: Laurentiu Munteanu - Business Manager Specialist – OSF Digital.
The impact that Salesforce Commerce Cloud Einstein is having on ecommerce is worth counting on. Discover how the power of “hands-off data” can multiply results for your business.
Salesforce launched Einstein in 2016 and with this celebrated product release came much relief to users who were drowning in data and seeking a lifejacket. Before Einstein hit the scene, users spent a significant amount of time and energy cobbling together information gained from reports and dashboards from numerous sources and manually sifting through a large volume of data. Some of this information was relevant; some wasn’t. Some of the data was duplicated - and well, most of the process was frustrating! The value of data was never a question for organizations, what was a concern was whether the data could be useful, rather than just be data for data’s sake. Could this information be something that could help an organization make better-informed business decisions? Add the bonus of being able to take a “hands off” approach in which machines did all the heavy lifting and well, it’s easy to see why everyone is celebrating Salesforce’s journey in bringing machine learning to optimize and supercharge the sales process for online merchants.
This article will specifically explore the opportunities that are possible with Salesforce Commerce Cloud Einstein and presents the case for why you should consider this solution as part of your ecommerce strategy. If you’re looking for a powerful and easy way to deliver highly personalized, smart experiences that convert, look no further!
Everyone’s throwing around the terms Artificial Intelligence (AI) and Machine Learning (ML) these days, but it’s important to note the distinction between the two. AI is the umbrella term for the research done into how machines are developing intelligence, whereas ML is part of AI which concerns itself mainly with software and how these algorithms are able to adjust and configure without any human involvement.
For online sellers, machine learning can help to quickly and efficiently fill in any gaps in knowledge that may arise in the merchandising process such as what to recommend to a shopper who is visiting a website for the very first time or what products are most likely to be purchased based on consumer purchase trends.
In time, a model is developed for each customer and from the learning gained from their preferences and behavior. Recommendations are created for each model and are filtered by specific business rules, for example, don’t show this person any clothing items under a size 4. Scores for each product in your catalog can be created based on how relevant the item may be to the customer at that specific moment in time. The individual model is based on the customers’ entire purchase and browse history and is modified in real time. The resulting customer experience from Commerce Cloud Einstein is one that is tailored to the actions a customer has taken on your website and adjusted as the shopper’s relationship with you continues.
Site management becomes automated helping you to take a backseat to actions that are well-informed and grounded in observations gleaned by technology. Leave the number crunching to the experts!
Commerce Cloud Einstein is a powerful ally to bring into your organization if you are looking to reduce your dependencies and cut down on tasks that take up a lot of time. Whether it’s creating new product groups, updating your segmentation, improving sorting rules or any manual merchandizing tasks – machine learning can free up you and your team to take on more pressing matters. Outsource the busy work and focus on what really matters in your business.
Personalization is the ultimate goal for online sellers as it delights consumers who are seeking a unique and tailored experience. Once enough data is captured for a customer, your website will develop the intelligence to provide buyers with immediate product recommendations that are most likely to appeal to them based on their behavior. They’ll also benefit from product sorting that is relevant to their interests as well as search results that directly relate to their needs. This activity is all done at every touchpoint and all channels where this kind of activity would both be meaningful for the consumer as well as be likely to encourage a positive response. Einstein product recommendations can be leveraged both online and in-store helping everyone to gain access to data-driven suggestions – not just authenticated users. Store associates will have access to upsell and cross-sell guides personalized to each customer.
Much like the temperature of porridge for the three bears needing to be just right, the same is true when it comes to the use of recommendations on a commerce site. Suggested products are meant to add to your customer’s experience, not be distracting or cause annoyance. Too few of them will cause you to miss the opportunity to promote the right item at the right time or may contribute to you losing the chance to engage in a conversation during the optimal time for this chat. It may be best to start with a measured approach and pick a few key areas where you would like to focus your efforts and then examine the performance of placing recommendations in these areas. Aligning this strategy with milestones for each step of your customer’s journey will help to ensure that all of your bases are covered.
As you can see, the benefits of Commerce Cloud Einstein are well worth exploring. If you are already using Salesforce Commerce Cloud, your investment is maximized by bringing machine learning into your business. It doesn’t require a large investment of time and if anything, actually saves you effort in the long run once you are set up. Speak with an experienced partner to discover how you can harness the power of this technology in your organization.