Sales teams cannot afford delayed response times, context-agnostic recommendations, or time spent on administrative activities. This is where AI becomes critical in sales. According to McKinsey Global Institute, AI will automate 45% of mundane work sales associates do every day. Furthermore, AI easily tackles challenges related to creating compelling sales pitches, prioritizing deals, and reaching out at the right time.
Here are a few ways how AI will enable smarter sales:
Automation of repetitive sales activities:
- Data collection: Chatbots on websites and voice assistants such as Siri and Alexa can collect basic customer data while they interact with brands without any human intervention.
- Lead qualification: AI helps to scour social media profile, Google alerts, and other data points to analyze the data and decide whether the conversation with the lead should continue, end, or be sent back to nurturing.
- Appointment scheduling: Personal assistants leveraging AI techniques in speech recognition and natural language processing can automatically schedule meeting times and places based on attendants’ preferences.
- Writing emails: If you’re familiar with Gmail’s smart response, then you get an idea of how AI based auto suggestions can cut down the time people spend composing emails.
Data analysis to surface insights:
- Identification of sales opportunities: By analyzing data from across the enterprise, AI solutions can identify potentially overlooked sales opportunities and create new opportunities in your CRM with recommended products and customer-appropriate pricing.
- Deal prioritization: AI helps analyze tons of deal related data including phone calls or emails to understand what behaviors and actions drive sales. Based on the analysis, AI will target and prioritize deals for engagement.
Prediction and forecasts:
- Deal closure prediction: AI uses machine learning to analyse historical sales data to find the correlation among the customer’s persona, your interactions with the prospect to predict deal outcome.
- Cross sell and upsell opportunities: AI algorithms helps to identify existing customers who are more likely to buy a higher end product of what they currently own (up-sell) and/or who are most likely to want a new product to complement their current purchase(cross-sell).
Brands are increasingly using AI to target the right customers and provide personalized service and recommendations. Here are 5 examples of AI is changing how brands interact with customers:
- Facebook: Using AI algorithms and machine learning, Facebook is enabling its machines to learn as much as possible about its users to create groups in most insightful ways for displaying personalized news feeds and ads.
- Netflix: Every show recommendation that pop-ups on your screen is driven by AI. Netflix leverages algorithms for analyzing viewing history of billions of hours of content streamed per month to not only recommend shows but also create new ones.
- Amazon: Using data from individual customer preferences and purchases, browsing history and items that are related and regularly bought together, Amazon creates a personalized list of products that customers actually want to buy.
- Harley Davidson: The American motorcycle manufacturer uses an AI program called Albert to identify and qualify leads before passing them on to a sales representative.
- Gogo Air: A company providing in-flight entertainment technology uses AI and machine learning to understand what products customers are using most and how they will be used in the future to predict customer trends and demand.