Consumer behavior marketing insights driven by machine learning
CUSTOMER INSIGHTS TOOL INCREASED SALES FOR LEADING SOFT DRINKS PRODUCER
Understanding Customer's Choices
A leading soft drinks producer was tracking customer and marketing data using elementary tools, such as excel spreadsheets.
The raw data gave them limited insight into their customers’ needs, choices and influencers, and limited knowledge in their £16 billion market.
To overcome this, they needed to improve their consumer modelling and analytical insights and deliver a data driven marketing strategy to increase their market share.
Consumer modelling is like a weather forecast. It predicts consumer behavior based on historical data to prepare you for a change in conditions.
Analytics is the conversion of raw data into useful information based on the data collected.
Understanding Data Relationships
The process of combining reports and evaluating data on separate tabs was both incredibly time consuming, but more importantly it made for very poor visibility on the relationships between data sets.
Without a data relationship, it made it hard to understand customer choices in real time.
They wanted to know when to compete for customers, when not to, and subsequently come up with an effective marketing strategy to better target and capture them moving forward.
The Data Analysis Bureau (T-DAB) worked with Fraction to build an analytic model and visualisation tool using a Proof of Concept (PoC) dashboard. It delivered data insights and recommendations for the soft drinks producer in real time. And highlighted the relationship between data sets.
For example, data highlights simple relationships between cold drink sales and hot weather. But also complex relationships, such as the demographic influences on single vs multiple product purchases, promotional influences or whether competitors’ options were present.
The user could input what information they needed, for example, ‘women between the ages of 18-30 in Central London’, and an automated data mining process and machine learning algorithm sorted through the datasets, returning key insights for the user to act upon.
The tool generated charts and graphs to illustrate important trends and insights on customers, and via the use of inferential statistics, could predict customer behaviors and market trends based on historical data.
Through automated data mining processes and the effective application of machine learning algorithms, they were able to focus their resources where it mattered.
It saved them critical time and uncovered hidden market, product and competitor insights, which they used to target specific consumer groups, market sectors and locations with an optimised marketing strategy.
Automated analysis saved time & made it easy
Automated reporting saved them time. It condensed hours and days of analysis into seconds. It helped them create a marketing campaign that boosted sales. And it gave them more time to discover hidden opportunities and marketing insights to beat their competition.
Better data insights improved targeting
Deeper insights provided the client with an opportunity to strengthen their market position. The data helped the client focus their resources in important areas and created a sale-boosting strategy that targeted specific consumer groups and market sectors.
The cutting-edge methods employed by T-DAB delivered more powerful and actionable consumer insight tools than off-the-shelf providers. And have enabled the client to understand and disrupt competitor trends