GOAL

FrieslandCampina’s Global Digital Team embarked on a mission to use digital data to guide their business instead of relying on siloed digital initiatives. The goals were to drive data-driven decision making across business units as well as to adapt the right approach for implementing pilot-based programs. As a result, growth of revenue was expected.

CHALLENGE

• While there is a wealth of information and data available, how to derive clear business decisions from these numerous sources and how to create links between them?
• How to ensure that deliverables will be not just another insight, but create real business value and drive positive change in how the company’s business is run?
• How to engage not just the leadership team, but the local teams who are working on the pilot programs on a day-to-day basis?

SOLUTION

From the initial insights, the Pulse dashboard allows TD Reply to track and measure performance of pilot approaches, foresee market developments and better prepare the market to adapt to these changes. The dashboard is also helping to replace expensive market data by better utilizing Friesland Campina’s owned data.

TD Reply successfully established a purpose-driven, data-focused and agile business consulting process, working from local “real-world” business questions:

• Gathering data from both, global and local existing sources,
• Building and running statistical data models and advanced analytics
• Providing actionable results to local senior management and global decision makers
• Estimating the “size of the prize” business opportunities when changing investments
• Initiating local pilot projects or “micro battles” based on model results
• Measuring pilot effectiveness and efficiency on key business outcomes (revenue, sales volume, market shares)
• Preparing roll-out within the market and globally

Within the first 18-months, TD Reply successfully run-through the above process in 6 key markets and 4 product categories.

GOAL

The project is driven by three main objectives set by Coca-Cola and CCEP Germany: 

1. Segmentation: Better and fully scalable segmentation of the Away From Home (AFH) market
2. Optimization: Providing guidance on how to increase outlet performance
3. Prediction: Create a data-driven model to predict and optimize sell-out

CHALLENGE

Creating a novel data-driven approach with datapoints, models, and tools that are fully scalable to different markets across the globe proved to be the main challenge.

SOLUTION

In the first step, by identifying and sourcing relevant publicly available online data, TD Reply discovered potential new outlets and helped Coca-Cola to grow the customer database. An intelligent model was created to pinpoint the most fitting potential new outlets from the sourced data, in view of brand fit and popularity. The model allowed Coca-Cola to analyse over- and underperforming outlets and identify the main business drivers.

Second, for each outlet, TD Reply creates a custom optimization plan, which identifies and prioritizes levers to actively influence outlet performance through in-store activations, promotions, and the optimal assortment mix.

In the final step, TD Reply developed a prediction model that analyzes what causes sell-out deviations over time to anticipate peaks and troughs in daily sales. The model can predict next weekly/monthly sell-out based on external factors, including seasonality, weather conditions, or local events, thereby reducing the out-of-stock risk. This also allows to improve the visit planning based on information on future events, optimizing the sell-in frequency and reducing unsystematic deliveries.

As a result, Coca-Cola and its bottling partners were able to:

• Reduce out of stock
• Significantly increase the quality and size of their outlet database
• Focus on outlets that really drive business success
• Defined key variables impacting outlet performance
• Drive brand building and innovation by knowing more about their outlet
• Optimize resource allocation for underperforming outlets with high sales potential
• Optimize sell-in frequency
• Maximize marketing impact

GOAL

• Measuring marketing effectiveness
• Data transparency and data democracy
• Build up data-driven competencies in the field of advanced data modeling

CHALLENGE

• Providing accurate measurements of media performance where the data available are incomplete.
• Identifying the most important levers for direct control of O2’s new customer business by analyzing 4,000 variables and 23 data sources.
• Achieving automated prediction modeling to quantify and measure media performance.

SOLUTION

A combination of the right data foundation and extensive modeling techniques allowed accurate measuring of O2’s media performance for both online and offline touchpoints. Nearly 9,000 employees have access to the Marketing Performance Management (MPM) dashboard, which acts as the single “source of truth” for all data relating to acquisition marketing. It quickly became a frequently used tool that marketing managers and other team members can use to quickly analyze campaign performance and media performance.

While most other dashboards are only of a descriptive nature, the MPM integrates smart data intelligence and gives predictions for all main KPIs. Moreover, Telefonica’s media management team was equipped with a new tool that fundamentally changed the way they work. There was a paradigm shift from gut-feeling to data-driven media investment decisions. The new budget planner allows users to select an optimal channel mix by integrating media-mix modeling results with an accuracy of 95 percent.

GOAL

The main goal of adidas was the development of a forecasting engine and ongoing measurement approach that:

• Can predict national footwear and apparel sales per sports category on a 5-year horizon more accurately and granular than existing forecasting data
• Delivers deeper insights into the underlying category drivers
• Can be scaled across key countries

CHALLENGE

• Finding a proxy for the overall market development across multiple sport categories (like soccer footwear or basketball apparel).
• Developing a prediction engine that is not only more accurate and granular than existing forecasting data, but also gives the client an understanding of category drivers.

SOLUTION

TD Reply improved the existing forecasting results at adidas by applying a hypothesis-driven, advanced analytics process and by integrating new indicators and data sources (especially digital soundbox data sources like google search data as well as macro-economic indicators) into an enhanced forecasting engine.

Category Sales & Search Matching: Identification of google search term pairings that proxy category sales data. Creation of proxied category sales from 2004 to allow highly significant driver analysis.

5-Year Trend Driver Identification: Using macroeconomic and independent search data ruling out autoregressive predictions to identify category drivers.

5-Year Category Sales Prediction: Applying ensemble effect (3 overlaying models per category) for stable and actionable predictions

The approach was developed and tested in the US as pilot market and is now rolled out across EU 5 markets (Germany, UK, France, Spain and Italy).

GOAL

• Establish data-driven thinking and a practice of improved insights sharing across department to break down data silos and to ultimately improve marketing efficiency
• Measure the digital perception of the various brands of the BMW Group as well as of BMW products in the digital sphere
• Understand the performance of BMW’s and competitors’ campaign and content in general to optimize continuously
• Enable holistic content creation and content management by observing and identifying trending topics in near real-time
• Create a central analytics touchpoint between departments and markets with potential for in depth analyses and data-driven decision support

CHALLENGE

Due to the size of the company and its complex dealer and sales network, the main challenges are of infrastructural, organizational, and cultural nature.

• BMW markets worldwide need to open and integrate their data for optimal use. This requires transparent and cohesive data collection and input processes.
• A lack of experience in working with data and even more important, taking decisions based on relevant insights, still presents a challenge to the project.
• As in other classical industries, the team had to cope with established thinking and behavioral patterns that did not necessarily facilitate data-driven practices. Existing communication and working mechanism as well as corporate processes, can also prevent fast and agile sprints, which are, yet, necessary for nimble and speedy project realization.

SOLUTION

TD Reply Berlin and Munich decided to approach the manifold tasks of the project by building a diverse team of experts in the fields of digital and data strategy, infrastructure set-up, and marketing analytics. To be able to cater to the different needs of these stakeholders, TD Reply went for a two-fold approach:

The heart of the project is TD Reply’s PULSE dashboard, an automatic go-to single source of information including all business-relevant KPIs. Each view incorporates only relevant KPIs as a data-driven KPI assessment with KPI effect modeling was the basis for identifying what is really relevant to the business. BMW employees can review campaigns, social media channel performance, product and brand perception, etc. around the clock and for a multitude of markets and business units.

The second building block constitutes a comprehensive range of special analyses. a dashboard user identified the need for further analysis based on the data in the dashboard. Other analyses assist in campaign platform selection, such as event sponsorships or commercial partnerships, white-spot analyses regarding consumer interests, or tracking of content fit, i.e. if a campaign and its consumer perception adheres to BMW’s brand values.

Both elements form the BMW Data Analytics Center – the go-to for every employee who wants to take better informed decisions and easily access the insights he or she needs.

RESULTS

With the BMW Data Analytics Center, fueled by TD Reply’s PULSE dashboard and business question analyses, BMW is equipped with valuable insights enabling continuous optimization of brand and product perception, content creation, campaign performance and other measures that help drive marketing ROI. BMW is now empowered to further established data-drivenness throughout the company and to enter the sphere of more advanced analytical projects, such as business effect modelling and predictive analyses.