Why are we talking about data-driven sales now?
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:
- Your sales team is increasingly intermediated from the end-investor, with data the link between the two.
- There are increasing sources of data and the overall amount of data being collected is exponentially growing but structuring this data is not keeping pace.
- A trend towards passives over the past decade is challenging the traditional sales approach; accelerated by the impact of COVID-19 which has seen a normalisation of sales meetings being held remotely. This means there is now less reliance on the physical location of your Sales team and investment specialists and hence ‘trip planning’ is rightly transitioning to a sales approach based on Client value.
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.
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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
What Types of Data Are We Talking About?
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
Alpha supports our clients in all the stages involved in becoming a data-driven sales organisation:
1. How you collect and structure data:
Your sales team cannot become data-driven without the capabilities in your architecture to collect defined, accurate, and actionable data
- Building your core data masters; Client, Product and the Client Book of Record (which links the two with meaningful flow & holding information).
- Structuring data against these masters and putting in place the governance frameworks to ensure their ongoing success.
2. What you compare it against:
Helping you articulate to your business why data is a strategic asset
- Embedding in your strategy – what are your measures of success and how can these be translated into shared goals across the team? Individuals need to be clear on the contributions that they make to this by taking data-driven actions.
3. What you do with it:
Data means nothing if you are not able to turn it into actionable insights
- Designing your data insight frameworks – ensuring this aligns to your existing sales strategy, processes and decision-making approaches (or managing any required changes to these).
- Tooling selection and implementation; landing data-driven capabilities and insights where Sales need them most. We can support with the front-to-back technology to support this; Data Warehousing, Analytics Tools, and CRM, Marketing & Sales Enablement Platforms.
4. Embedding and enabling continuous improvement
- Establishing your data-driven vision and designing an operating model that supports continuous training and improvement. Data-driven sales is not a one-time activity and therefore need to be self-sustaining.
To learn more about how data can accelerate your sales strategy, reach out to our Distribution specialists.