How can Predictive Analytics can Help Boost Your Sales
Predictive analytics takes CRM data and uses it to make predictions about future events. In terms of sales, predictive analytics looks at information from the entire customer life cycle to predict how customers will behave, such as whether or not they will convert.
As technology evolves and the world becomes more engaged digitally, you need to know your customers and prospects better than they know themselves. This helps you tell them what they need well before they realise it on their own. By leveraging CRM predictive analytics, businesses are able to connect and engage with existing and potential customers in a new and much more effective way.
Predictive capabilities have always enamoured humankind - from astrologers to data scientists. Just like our galaxy – there are patterns, clusters and trends in data, which hold astronomical value for businesses. Data driven insights could be descriptive, prescriptive or predictive and in this article my focus is Predictive Analytics. Stated simply, predictive analytics analyses current and historical facts to make predictions about future or otherwise unknown events, using patterns found in historical and transactional data.
The business value of predictive analytics
While your sales force is the best judge of whether or not your organisation will win a deal or how successfully (or poorly) an opportunity is progressing, there are a host of data-related challenges that they face that hinders them in making the right sales decisions. Some of the top challenges include:
- The presence of humongous amounts of customer data – with practically no insights
- No access to valuable data that can help improve forecasting accuracy
- Absence of predictive capabilities in modern tools that results in disconnected experiences – with reduced productivity and increased inefficiency
- Incompleteness of CRM data in systems hampers good quality predictions (machine learning tools learn and train from complete, useful, accurate data)
- Data being tied to monthly and quarterly business tasks (data is typically entered during specific times, leading to insufficient real-time data)
Predictive Analytics in Sales - The Right Data Management Strategy
Predictive analytics is pretty simple on the surface. It’s the practice of analysing data from past events to try to make predictions about the outcomes of future events. Of course, things are a little more complicated than that. Analysing Big Data to generate predictions about future events requires powerful software and lots of data. However, the impact it can have for a business — especially a sales-centered one — is huge.
Here are ways predictive analytics can help boost your sales:
1. Find the hottest leads for your sales team
According to a report by BusinessWire, 90% of B2B merchants expect e-commerce sales to increase by the end of 2019. Thus, you should also use the predictive analytics tools or collaborate with an expert who can build you one.
You can successfully know in advance what your customers are most likely to buy and hence provide prescriptive products and place your content likewise:
- You can, to a great extent, determine the highest price a customer will agree to pay
- You can initiate target recommendations, promotions, and plan a better price management strategy
- You can improve your supply chain management, warehouse management, and logistic
2. Predict Buyer Behavior
Categorise your customer base. When doing so, it's important to use a wide range of characteristics. Consider demographic traits such as gender, age, and location, but also be sure to include engagement tendencies like web activity, preferred media channels, and online shopping habits.
Each customer persona will have its own unique reason for choosing your business, and it's imperative to identify it. Look beyond just the product or service, and consider the external factors that influence the customer's buying decision. For example, was the purchase made out of convenience? Or did the customer make a conscious decision to seek out your brand? How urgent is the purchase, and how much does the customer want to spend? Thinking about the context of the customer's needs is a great way to determine where you can improve the customer experience.
3. Generate accurate buyer personas for targeted marketing
Buyer personas help you understand your customers (and prospective customers) better and make it easier for you to tailor your content, messaging, product development, and services to the specific needs, behaviors, and concerns of different customer groups.
For example, instead of sending the same lead nurturing emails to everyone in your database, you can segment by buyer persona and tailor your messaging according to what you know about those different personas and their appropriate stage of the sales cycle.
Here are types of customer data that you might want to consider before you are breaking down your leads persona:
Make the most of these predictive analytics tools by offering a way to engage with clients, learn more about individual opportunities, and improve sales productivity and customer satisfaction. With predictive analytics, you can take your CRM game to the next level and enjoy unprecedented profits in the long run.
Metisc is one of the leading Dynamics 365 providers and can tailor the delivery of your online experience. We can build a personalised dashboard, customised homepage, and B2B predictive marketing analytics platforms by integrating Dynamics 365 with Power BI tools to leverage Big data and predictive analytics to accelerate your B2B sales.