Sales success hinges on the ability to understand trends and create accurate forecasts. Sales executives, managers, and representatives all require clear and consistent insights to understand how their sales representatives have performed to-date, how their teams are tracking towards quota, and which opportunities to prioritise and act on.
While Salesforce, for example, tends to be one of the tools of choice for recording prospective customers’ interactions as opportunities progress through the pipeline, this tool on its own isn’t enough to get a complete picture of the sales lifecycle. Additionally, data within such tools is populated by sales reps, which means it’s often inaccurate, or incomplete. Not only do sales managers have to aggregate and analyse the data, they also have to maintain data integrity.
Think about all the pieces involved in the sales funnel. Website visitor activity lives in applications like Google Analytics, while other tools, like Marketo, show how prospects are nurtured into marketing qualified leads, and then CRM tools show how leads are converting into opportunities. Each of these is just a piece of the whole sales funnel picture, and were designed to do their individual part of the process. This means they are not really aware of functions outside of their realm, so collaboration between them is limited to often poor data integration.
So, how do you get a global picture of your sales funnel, and how can you answer a question such as "how many more leads will I need to get to increase my sales by £2 million?” These individual applications can't answer these questions because the question addresses the whole value chain.
That’s where embedded analytics comes in.
Embedded analytics is the integration of data analytics capabilities within business applications. By integrating data analytics capabilities from multiple systems within a business application that teams already use on a daily basis, you can give your sales managers a complete view of opportunity information and translate all your sales data into actionable insights.
Embedding analytics into the applications workers use every day grants them a much more seamless experience, because they don’t have to access multiple tools to find the data they need. By embedding analytics deep within a single application businesses can empower their employees to create and share dashboards, reports, and visual analytics across their organisation, with little to no support from IT. On top of that, dashboards and reports can be designed in such a way that people of all skill levels, from business users to data analysts, can easily access and understand them.
This is in contrast to traditional business intelligence (BI), which extracts insight from data within the silo of an analytics tool. Embedded analytics strives to bring insight and action into the same context by integrating analytics deep within business applications and workflows.
What Should a Sales Dashboard Look Like?
Some people think of embedded analytics as simply a reports module within business applications, but it’s much more than that. It means embedding analytics deep within the application experience, so users can both view business data and take action based on that information all within the same workflow. It means creating a better experience so users become more efficient in the way they work every day.
For instance, instead of just viewing open opportunities in a report, businesses should embed a dashboard that shows the forecasted sales based on historical sales rep win rates and pipeline stage methods. You can also compare your forecast projections against your goals to see whether your current goals can be met. A sales manager might also want to exclude any number of opportunities to see the effect on the pipeline. By embedding their analytics into an existing application, a manager could easily discount opportunities that might not close.
You can also create a dashboard that helps sales managers be confident in current opportunities, and identify which high-priority opportunities to focus on. This dashboard can include the conversion rates between sales stages, and the shape of the pipeline by deal count and value.
Historical information can also be helpful, but is a pain to pull out and analyse, and most people end up exporting to tools such as Excel. By embedding something such as an historical sales dashboard, managers can review past won (and lost) opportunities to understand sales cycles and past behaviours. For instance, how is the team doing this quarter versus last quarter? What are the historical trends? This can also include how many deals were won compared to how many were lost for a given time period, showing the win rate over time.
Now, these dashboards should contain more than just numbers and lists; they should display the data using easy-to-understand visualisations such as bar charts, line graphs, and even concept word clouds. To avoid information overload, these visualisations should also allow users to drill down into the data using filters. For instance, you can break your historical sales data down by sales representative, product, segment, industry, or geography.
By delving deep into the data, sales managers are able to evaluate, manage, and improve sales performance. In turn, they can coach their sales representatives—who also have access to the data, though maybe at a lower level—to take the appropriate actions to meet team goals and optimise win rates.
From prioritising selling efforts and deal activities to maintaining sales pipeline health, embedded analytics is a proven way for any organisation, no matter what type or industry, to drive sales success.
By Tom Cahill, VP EMEA, Logi Analytics
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