Data-Driven Sales: Using Data to Accelerate Your Advantage in the Sales Cycle

We are certainly not the first to talk about data – it is hard to avoid ‘data’ being mentioned in any conversation throughout the functions of an asset manager. But let’s consider today’s operating environment to justify why it is more important now than ever:

Data-driven sales won’t ever replace the skills of your experienced Sales teams. But in an environment where the top-down strategy is to grow assets without growing headcount, data needs to fill the gap: sales teams need to make decisions better, faster, and more consistently and get in front of the right prospects and clients.

Sales teams across the industry often express their frustration to us that they have too much data presented to them – but all too often it is not tactical or is in an inconsistent format that makes it hard to establish which action they should actually take. Simply presenting the raw data is not enough.

As a metaphor, consider Formula 1 drivers. They too operate in an environment that is increasingly levelled, as the specifications of their cars become less differentiated. Yet, their teams nevertheless create a winning advantage by processing huge amounts of data and presenting it to the driver’s cockpit in real-time and in the most useful format possible.  The driver is still taking the action and remains the face and personality of the team, but success is increasingly down to the synergy created between the person in the seat and the information made available to them. Increasingly, Sales teams in asset management likewise stand out as a result of the data that supports them.

A successful data-driven Sales strategy should not feel retrospective. This risks distracting the Sales team from spotting opportunities (by spending effort trying to articulate what happened and why). Alpha’s view of the industry has found successful managers centralise the complexity around data mastering, and replace manual processes (such as ‘trade claiming’) with automatic alternatives based on rule-based logic: freeing up Sales team capacity to test the quality of the forward-facing data insights and calls-to-action that they are presented with.

In this article, we will consider some practical applications of a data-driven sales strategy and some ideas on how to get started or continue on this journey.

My Next Best Sales Action

Continuously improving sales efficiency through algorithms that deliver sales insights and calls-to-action

• Our objective here is a ‘Sales Cockpit’ for your Sales Teams that highlights to them prospects and clients that have the highest propensity to invest and allows them to initiate the most relevant sales process with ease; whether that be a courtesy call, tracking an opportunity or serving them some intellectual capital
• Sometimes delivering these call-to-actions will be a case of streamlining existing, time-consuming processes that already exists across the sales team; for example, mobilising a sales effort when a new product launches. Others might be more subtle, and dependant on interrogating the underlying data more deeply; for example, if we can identify the underlying Adviser responsible for an intermediated investment flow should we prompt the relationship manager to schedule a follow-up conversation to further explore that Adviser’s propensity to invest?
• Data Insights and their calls-to-action must be designed to learn and self-improve; allowing the Salesperson to rate the quality of the insight provided. We can then look at this feedback in aggregate to understand how the call-to-action algorithm can be improved. Simplistically, an algorithm is just an opinion embedded in code, so we must find the most frictionless processes to get the opinions of the Sales team represented back into them. Without this feedback loop, there is a real risk that they will soon become ‘white noise’ and actually be a distraction to the Sales team.

Please get in touch if you would like to receive the full article which provides further detail on all the stages of the Sales Cycle

How can Alpha help?

We recognise the importance of beginning the journey to become a data-driven sales organisation in the right spirit:

• Be Agile; What you tackle first should be driven based on the priorities of the sales team; ideally, with the use-cases you deliver being championed by the sales team themselves.
• Whilst getting the right underlying data architecture in place is fundamental to much that can be achieved in data-driven sales; the underlying data, and ‘what can we do with this?’ conversations, should not create an environment where this drives what is pushed onto the sales team.
• Not everything will work out the first time. It is best to fail-fast, learn and move on