Analytics is a great way to improve results and anticipate future performance so that you can act. You can use past and present data to analyse the trends and behaviour of your ideal customers, which will allow you to be proactive, anticipating results and future behaviour based on data, not assumptions.
That said, analytics terminology such as AI, predictive analytics and machine learning can be mind-boggling. Explanatory articles often do not explain how implementing any new system or process will deliver better outcomes. We all think we know what these terms mean and how they might apply in various situations, but what is the benefit for your business?
Let’s start with marketing at the top of the sales funnel
Simple data analytics is the key to unlocking the most value you can extract from data about your customers and prospects. When analytics is used to segment customers, marketers can make more informed decisions about targeting new opportunities. Segmentation might be based on buyer needs, organisational demographics and more.
Identifying competitor activity, market patterns, and trends will help you assess future buying patterns. In other words, analytics and business intelligence can help you evaluate which customers will most likely buy your product or service.
The middle of the funnel
Both marketing and sales can use lead scoring and performance against best practice models to decide on the communications that will achieve the highest interest and encourage loyalty. They enable better sales performance by highlighting past trends in customer behaviour and allowing marketers to plan campaigns effectively.
On customer retention, marketing teams can use analytics to consider data collected about past customer behaviour to anticipate the best action for customer communications.
Bottom of the funnel/sales forecasting
Very few companies nowadays exist without some method of sales forecasting. Historical data, combined with an understanding of forthcoming marketing activity, can be used to assess how much revenue a relationship will likely generate.
Tying your marketing activity to the sales effort and analysing performance against KPIs will lead to an end-to-end focus on the sale funnel, which might include, for example, marketing keeping selected prospects ‘warm’ with loyalty communications. At the same time, sales focus on closing out immediate opportunities.
An end-to-end approach will help to reduce risk, improve outputs and increase revenue.
Advanced solutions
All analytics can, to a greater or lesser extent, help you to predict what might happen next. Introducing computer-based algorithms (predictive analytics) moves the focus from what has happened to real-time calculations on future performance and unexpected problems.
In B2C industries, artificial intelligence (AI) and machine learning take this form of analytics to the next level by learning critical aspects of customer behaviour and individual preferences and better-predicting purchases and interactions. For B2B organisations, where the sales cycle is often longer and reliant on the quality of personal relationships, the benefits of AI and machine learning are, in my opinion, still to be proven.
In summary: optimising your pipeline to win more
Analytics can help you:
Optimise existing marketing and sales processes
Understand customer behaviour better
Identify prospect opportunities and
Anticipate any problems with the sales funnel before they occur
All organisations can benefit from collecting data on customers, markets, and prospects and then using that data intelligently to predict the best next steps, optimising the pipeline to win more. Where data analytics provides conclusions from past events, with experience or more sophisticated technology solutions, it can also provide actionable insights to better serve your customers and prospects.
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