Provide your sales team with high converting customer data

How to create predictive analytics app and drive a data-driven approach to sales and customer retention with Low-Code and see results fast.

6 minutes read | by Lee Smith | 21 October 2021

Traditionally, sales has been a dark art. Those in the sales industry have relied on their intuition on where to find the next deal, and which accounts are more likely to convert into sales. This approach works; however, it takes time for a sales rep to research the customers problems and have multiple conversations to determine whether they are an ideal customer.

Today, businesses need to make decisions fast, and this approach doesn’t lend itself to being a particularly agile solution to growing sales or retaining customers. Lots of time and money spent on wasted calls.

Any business with large volumes of customers already has the ingredients to increase sales at their disposal, but most are not utilising it.

So, what is this secret ingredient? Data.

Customer Sales Data

Locked away in your CRM systems is a wealth of information on your customers just sitting there waiting to be utilised properly. Average sales value, contract lengths, contract end dates, customer demographics, support calls. It’s all in there.

The difficulty is knowing where and how to access the data. Ask your sales team if they know how to access and analyse the data and I’m sure that most of them will say that they don’t know how to.

Before we get on how to access and analyse the data, we should first look at how to approach the transition to a data-driven approach to sales.

How to become a data-driven sales organisation

The first, and arguably the most important step is to consider your business objectives. This step isn’t about the data or how to access it. This is what you want your sales function to achieve.

Example: We want to retain more existing customers at the end of their contracts.

Once you have your list of sales objectives you need to look at the metrics that you have recorded in your system that will help you to identify the customers or prospects that are more likely to convert.

When trying to identify the data points its useful to have a list of questions that need you need answers to.

Example: How many customers leave at the end of their contract? How many customers that have used customer support re-contract? Are online customers more likely to churn?

Now you have a list of objectives, a list of questions and you know what data is required it’s on to the how. How do you extract the data that matters?

Accessing the data goldmine

Now to the difficult part. Accessing the data to analyse it.

Most CRM systems will have the ability to mark records for export. That’s great, but it will need a spreadsheet wizard to create a solution that can filter the data. This method will also rely on a manual process to select the records that you wish to export, which is time-consuming and prone to failure. Spreadsheets also have their limitations especially when it comes to volumes of data. Remember the fiasco with missing Covid data during the recent pandemic? Read more in our article here.

So, what’s the alternative?

Building a data-driven sales tool

One alternative would be to utilise a Low-Code platform to create a bespoke app to connect into your systems and automatically analyse the data. This app will distribute lists and tasks to the sales team and track the success of the selection criteria against sales.

There are many advantages to using a Low-Code application, over trying to manually create spreadsheets or dashboards in your CRM.

The first is that ability to integrate data from multiple sources, not just the data that you hold in your CRM. The more complete you can make the data on your customer the better.

Secondly, implementing a Low-Code application is much faster than traditional development methods. Whether you choose to outsource the development of a solution, or you want to build the solution in-house, Low-code utilises drag and drop functionality to make system connections, create automated workflows and build screens.

Enter PhixFlow (and our data superheroes!)

So how might a solution look like. Let’s take a look at a real-world example of a data-driven sales approach.

In the telecommunications industry, there is a high turnover of customers at the end of a contract, as most customers will shop around. Add in the complexity of Ofcom regulations which require the provider to communicate with the customer that their contract is coming to an end and what the cost implications are if they do nothing, and you have a recipe for customer churn.

Our customer, a fibre broadband provider in the UK, needed a solution to improve the efficiency of their outbound sales team and increase their customer retention rates. To do this, the sales team needed a list of customers who had a high propensity to churn at the end of the contract, but would be more likely to re-contract with a proactive approach prior to the contract expiry.

Download our free guide and unlock the potential from your data

Data Potential Download

Form to pass details to Force 24 and re-direct to the Landing Page
  • This field is for validation purposes and should be left unchanged.

Predictive analytics

Using the PhixFlow Low-Code platform, a predictive analytics application was created. Data was extracted from their CRM, billing platform and customer support system. This new consolidated dataset provided the basis for a comprehensive view of each customer.

The next step was to build an analysis model that graded the customer’s propensity to churn at the end of their current contract. Key factors such as how the monthly tariff, age, number of previous contracts, products purchased and acquisition channel were all taken into consideration. Each customer was given a score and a report created to show those with contracts expiring in the next two months and are most likely to leave. This information was overlaid with analysis of how likely a customer was to call retentions at the end of their contract. Customers who were likely to leave but unlikely to call retentions themselves could be targeted by an outbound team to intervene before a customer was presented with an end of contract notification.

This list of customers was then fed back into the sales CRM and tasks allocated to each sales rep to contact those customers.

The results. Customer retention increased and a happier, more efficient, sales team.

Grow your business with a data-driven sales approach.

No one likes to waste time, money or resources and relying on long sales cycles. Endless phone calls and sales intuition will do just that. Utilising data is your new secret superpower (no special outfits required!) and made possible with Low-Code.

Get started with a demo of PhixFlow and discover how become a data-driven sales organisation.