In this opinion piece, SalesPreso co-founder and CMO Joel Thomson explains how B2B companies can use their data more effectively and deliver a personalised customer experience that matches their B2C counterparts.
From the Cambridge Analytica scandal to the EU’s recent GDPR legislation, this year has prompted individuals all over the world to consider how their customer data is shaping the way brands engage with them, but what about the brands themselves?
So how can B2B organisations use their data more effectively and deliver a personalised customer experience? Having worked with some of Australia’s largest and most successful B2B organisations at SalesPreso, I believe it comes down to four key factors.
Define what constitutes meaningful data for your customer
Every B2B organisation wants to demonstrate they know their client’s industry. That doesn’t only mean high-level insights on similar companies or the industry in general. Instead, generate relevant data and explain what that data shows. This could be your knowledge of trends, geographic, or behavioural data – whatever it is, it must be useful and actionable.
Your data needs to demonstrate that your organisation understands the kind of problems the people in the client’s industry have and that you can connect that insight to support a recommended solution.
Our client MYOB, for example, takes industry data showing the time taken to complete business-critical compliance tasks and overlays that with their own data for a single customer. The combined data illustrates the benefits of using one or more of their products, creating compelling reasons to purchase these products.
Translate the data into valuable client insights
Edwards Deming once said: “Without data, you’re just another person with an opinion.” I’d say without an opinion, you’re just another person with data.
The data is the proof. Critically, it’s the context for an insight or opinion that can drive a customer action.
We have seen companies invest millions of dollars in business intelligence systems designed to surface business data in reports to help the marketing and sales teams. To maximise the investment made in getting that data, it needs to be more than accessible – it needs to be digestible.
For example, while Telstra has been able to surface granular business customer data from multiple systems for years, its challenge was in getting meaningful customer insights from this data in order to inform decision-making around renewals and new products. It’s been able to overcome this with an AI engine that automatically matches their data with understood behavioural patterns, and can then suggest insights and associated products and services.
Automate everything you can
The greatest challenge we’ve seen for organisations with data and the salespeople who need it is the enormous amount of time required to get that specific data and define what insights will help propose a relevant and valuable approach to customers.
This often means that data is used more for internal research and decision-making rather than getting out in front of customers – a missed opportunity given customers today have already researched your product or service and don’t want to ‘be sold to’, particularly the Millennial demographic.
Automating access to data means that all customers, new and existing, large and small, will get a tailored experience and be far more likely to respond to recommended actions. REA Group, for example, has been able to automate access to all of the industry, geographic and specific customer data they need to sell with, reducing sales prep time by up to 60 per cent.
Continue to reassess what data supports your business outcomes
Once you’ve set up these systems for success, be vigilant about tracking. Set up clear KPI metrics and track what data meets them, and ensure the data sets continue to drive actionable insights – not just adding to customer (or internal) information overload.
Data-driven marketing, selling, and advertising is only going to increase, and there will be more and more data sources. The challenge is knowing how to use the data – know the customer and their context well enough to automatically generate insights that will actually affect their business, and drive their engagement with you.