How VodafoneZiggo is harnessing AI to boost sales operations
November 30, 2019
From sci-fi movies to real life, AI has made a significant leap into becoming a pioneering technology, an invaluable tool for every organization. The story of how VodafoneZiggo applies AI and data science to pivot to a data-driven customer approach will show how AI has revolutionized the sales industry and secured its prominence in the business world.
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Twenty years ago, artificial intelligence (AI) was the stuff of sci-fi movies. No one could’ve guessed that one day, AI would be very much in use - predicting what Netflix shows we want to watch next or which type of pizza we are most likely to order. Today, AI is a part of everyday life and has turned into an invaluable tool that organizations can use to accurately predict consumer behavior.
When VodafoneZiggo approached us to discuss opportunities in the sales domain, we suggested using the power of AI and data science to help approach their customers. We developed a predictive model and fed it historical sales data to determine lead potential. This allowed sales agents to focus their effort on the most promising leads and define the most effective sales strategies, ultimately outperforming the previous model in the sandbox with a drastic increase in conversion rate.
We’ll explain to you how AI helped to pivot to a data-driven customer approach, and how you can practically apply this technology at each stage of the customer lifecycle to make smarter sales decisions.
You may have heard about AI and data science, but what exactly does that mean in a sales context?
Some practices have made their ground in the sales world: a bulk approach based on leads and zones 'cooling down', propositions based on the available products and the sales rep’s gut feeling. However, VodafoneZiggo was looking for a way to target customers who are actually welcoming new offers—improving the experience of sales reps and customers alike. They felt that the knowledge of their current customers might help with this mission.
So, VodafoneZiggo approached us with a simple task: help them figure out how to leverage CRM data in order to focus their finite resources on the most promising leads.
Our combined team of data scientists got to work on designing a solution that utilized AI to our advantage. Data science is about predicting the future using historical data: in our case, we proposed combining several customer data sources as input for our AI model. When validated and tested, this model calculates a score by which leads to put priority and focus on.
VodafoneZiggo is among the front-runner companies that grasp the benefits of using AI in their sales strategy. AI is on its way to be the top growth area for sales teams—with a potential rise of up to 139 percent in adoption rate over the next three years. This technology has the potential to increase your efficiency tenfold, giving you and your organization the competitive edge when it comes to directing time and resources in the right places.
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AI is on its way to be the top growth area for sales teams
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Using Salesforce data as a foundation, we combined several data sources into a complete data-set: a Customer Analytical Record (CAR). From there we built and trained a predictive model to score individual leads as well as groups of leads (zones). For this, we used a combination of R and Salesforce Einstein. The hypothesis we set out to prove was that historical variables could be leveraged from past sales data to identify high-potential leads, allowing the sales team to focus their efforts more precisely.
After training our model, we unleashed it on our test data. We set up an experiment to check the accuracy of the model, by comparing the lead scores with actual sales results.
The result? High-scoring leads outperformed the status quo by nearly a third. These outcomes far exceeded expectations and demonstrate just how powerful the emerging tools of AI and data science can be. VodafoneZiggo is currently conducting field tests to further tweak the model and expand its use in daily operations, with an increased number of orders as confirmed steady outcome.
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In the above described case, we implement a predictive model to determine where to focus sales efforts and ultimately improve new business. However, it is viable to involve the technology in various ways across the customer lifecycle, making it an invaluable tool for any sales team.
When it comes to obtaining, keeping, and winning back customers, any organization can utilize AI to determine effective actions to take at every stage:
Like any business transformation, VodafoneZiggo’s transition to using AI and data science led to some valuable lessons learned along the way. Below you’ll find some general guidelines to help you successfully implement AI into your sales strategy.
Lesson 1: Collect data across organizational barriers. It may seem obvious but in order to conduct data science, you need data. In our client’s case, we built their entire AI tool based on the data collected across CRM systems and many other sources. The more complete and accurate the information, the more holistic the picture of your customer is and the better predictions the tool can make. To this end, it’s wise to bring down the silos of data sitting in your organization and gather all teams to pool information. Each team has different goals, resulting in many different types of customer information.
Lesson 2: Build a space to experiment in. Many companies avoid risk. The word experimentation can incite fear into the minds of organizational leaders. However, it is also an opportunity to find new revenue streams or ways of reducing your operating costs. The key to building this space for experimentation is keeping the focus on testing value-driven hypotheses and discarding initiatives that do not contribute to business value. In the case of VodafoneZiggo, we set up a sandbox where teams could experiment with data to see if AI helped achieve a specific goal (increased conversion). Once the effort proved promising, the decision was made to go from proof-of-concept to model deployed in production. This type of purposeful experimentation and actionable results can drive huge leaps of innovation within your company.
Lesson 3: Deploy the model after it has proven its worth. An AI model cannot generate value if it remains in the experimental stage. Productionizing comes with considerations like cloud vs. on-prem, maintenance and future development of the model, embedding the output in a new way of working (change management!). Think about how you eventually want to use the model: if it’s meant for empowering your marketeers to make data-driven decisions, you probably need a different tool than when it’s about a probability score that will serve “under the hood”.
AI and data science open the door to facilitating and boosting sales. We are proud to partner with our client VodafoneZiggo in exploring the possibilities of this cutting-edge technology. At the end of the day, our goal is to make our client’s businesses run better and prepare them for the exciting future of technological advancements ahead.
With VodafoneZiggo’s success in implementing AI, the door to new sales strategies and processes is now wide open. We are excited to see what the future holds for our client and anyone else who is willing to unlock the potential of these emerging tools.
Can’t wait to streamline your sales strategy and unlock the potential of AI for your organization? We are here to help!