Comparing AI Tools: Salesforce and Dynamics 365

Just a few years ago, cloud computing revolutionised customer management, allowing small to mid-sized businesses to access communication platforms and data without having to invest heavily in a complex IT infrastructure. But with the advancements in AI, machine learning is the new kid on the block. This new technology can transform marketing and customer support, and now they’ve been introduced in to Cloud CRM tools by the likes of Salesforce and Dynamics 365.

The amount of data we are creating hides great sales and business growth opportunities, however without the help of AI, limited human resource struggles to truly grasp, analyse and use the data. For the majority of companies data science is an absolute struggle; collection, management, data wrangling, employing rare data scientists, etc. Luckily though AI is here (unfortunately not human-level artificial intelligence… yet) to help scale efforts by sales teams by extracting useful information and patterns from data and to find the most useful and successful courses of action.

AI tools in the CRM are useful from the off-set. The AI capabilities analyse and predict what leads will turn into opportunities and what opportunities will become customers. Furthermore, there are tools that make valuable suggestions for marketers and salespeople like telling them what opportunities have been neglected, to predicting when an email will be opened by a customer.

But, how do the AI capabilities in Dynamics 365 and Salesforce compare?

AI features in Salesforce and Dynamics 365 are very similar at a first look. Dynamics 365 has AI tools built into their standard workflow, while Salesforce has particular tools available in its different offerings.

Relationship Insights in Dynamics 365 automatically captures data from emails sent and received in Office 365 to do sentiment analysis and lead scoring, presenting and showing you strength of opportunities as well as how healthy relationships are. Furthermore, it shows you what risks to deals there are, such as where competitors showed up and what the best next action is. For analysing the health of your relationships with your customers, Bubble charts help you prioritise. The system provides you with alerts for customers willing to meet and relationships that are deteriorating.

Fields get automatically filled in with predicted data and information, such as what products need to be restocked, what needs upselling or cross selling, etc.

The Sales Cloud in Salesforce has very similar features. The Predictive Lead Scoring is there to suggest what leads are most likely to convert. Salesforce’s Opportunity Insights let you know when deals start appearing weaker or stronger, where competitors were mentioned in conversations and even notify you that you may be talking to someone who doesn’t have the power or authority to finalise the deal.

Dynamics 365 uses machine learning to suggest products based on click patterns, previous orders and wish lists. It also personalises what information is visible basted on each customer.

The same sort of predictive data can be found in the Salesforce Service Cloud Recommended Case Classification. This fills in fields automatically so cases can be directed to the most relevant staff. Furthermore, Predicted Close Times predict the duration of issue resolve and Recommended Responses present the type of information that should be used when responding.

In both systems, there’s an element that recommends relevant articles and topics in the industry. In Dynamics 365 it’s available through Microsoft’s Azure ML service that suggest Knowledge Base case studies and articles.

Salesforce’s Commerce Cloud also does the same thing. It creates personalised suggestions as well as the order products are shown in and what shows up in searches. Furthermore, Commerce Insights suggest associations to explain buys, as well as the channel used to reach customers, and how they buy (whether it’s after opening emails, etc.)

The Customer Insights tool in Dynamics 365 is largely similar to the Einstein feature in Salesforce. Both capabilities allow to pick KPIs or measures (profitability and cost) and to see associations and insights. Customer Insights presents findings through Power BI visualisations, while the Salesforce feature produces PowerPoint and Word documents.

Businesses already generate tons of data and it is already accessible, however by using machine learning and AI in your CRM you’ll be able to speed up reaction and responses, ensuring that there aren’t as many missed opportunities. While there’s a lot of talk about the “customer journey” in today’s business talk, few companies actually have a strategy in place in their marketing and sales processes. These tools will help you improve to no end.

Whether you use Microsoft of Salesforce, the intelligent capabilities they’ve added won’t replace your customer or marketing teams, however they’ll help make them more effective. AI is here now, so make the most use of it, because one thing’s for sure, your competitors will be.

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