BMW – BRAND IMPACT ACCELERATOR

PERIOD 2021 – ON GOING

Strategically fueling and transforming a brand necessitates precise brand activation management aligned with defined objectives and a multifaceted assessment of brand impact. The Brand Impact Accelerator (BIA) empowers BMW campaign and experiential managers to make informed decisions and foster a culture of learning within the organization. Over the past few years, we’ve critically evaluated more than 50 brand activations, ranging from ArtBasel to the IAA, to assess their strategic brand impact and utilize these insights to enhance the efficacy of future activations.

GOAL

The BIA program was designed to achieve three primary goals:

Goal-Oriented Management: :

Establish a goal-driven steering process that engages all pertinent stakeholders.

Unified KPI Framework:

Create standardized Key Performance Indicators (KPIs) for strategic and tactical activation management.

Granular Brand Image Measurement: :

Develop measurement constructs that enable a detailed assessment of the BMW brand image.


CHALLENGE

The challenge lay in crafting and implementing a data-driven approach that aligns with event and campaign managers, channel owners, the BMW in-house agency, The Game, as well as the KOL agency. We aimed to cultivate a data-driven culture within the BMW Brand Impact Council.

SOLUTIONS

Shared Vision:
We embarked on defining a collective vision spanning the entire brand communication landscape.

Stakeholder Alignment:
Identifying key stakeholders and uniting them behind the common vision, approach, and KPIs. This involved defining KPIs and constructing measurement frameworks based on digital data, such as organic searches on both event and brand levels, and Digital Brand Equity, a measurement derived from social listening data assessing various facets of the BMW brand image.

Reporting Framework:
We established structured reporting formats for pre-event, during-event, and post-event evaluations. This included building a dynamic dashboard and a benchmarking database.

Learning Culture:
Our efforts extended to fostering a culture of continuous learning within the organization.

Future Positioning:
We also explored opportunities for positioning BMW within the broader competitive landscape.

By implementing the Brand Impact Accelerator, BMW has achieved a more streamlined and data-driven approach to brand activation, enhancing the brand’s strategic impact and aligning all stakeholders behind common objectives.

BUSINESS TRAINING FOR DATA SCIENTISTS

PERIOD: 2017

GOAL

  • Enabling Data Scientists to provide business impact by understanding company stakeholders and their business challenges
  • Providing stakeholders with relevant insights and analytics solutions, that can be used on a day to day basis
  • Leveraging the available data to explain consumer behaviour

CHALLENGE

  • Making Data Scientists understand the importance of the business perspective to provide analytics insights and solutions with impact on business
  • Helping Data Scientists to change the perspective from an analytics and data focus to a stakeholder/business and consumer focus
  • Providing a structured education program that is giving the relevant theory and its application to real-world business questions

SOLUTION

We developed a training approach that is providing skills in the area of business, communication, and applied analytics (understanding of data & business analytics) as well as a framework that can be used to work with different business stakeholders on data science projects. The learning sessions were accompanied by use cases the data scientists were working on, which were chosen by the company. We provided on-site sessions as well as online consulting on the projects the data scientists were working on over a period of 3 months.

This approach has been shown success in a sustainable impact on the work of data scientists for different clients. The data scientists learn to understand stakeholders and how to manage them within a project, to develop a research and analytics approach from a business and consumer perspective, the analyse data with a focus on actionable insights, and how to present and visualize the results to business stakeholders. The project helped the analyst of the client to better understand their role and the expectations towards them within the company and to provide analytics with business impact. The company use case helped to significantly increase the ROI for online media channels.

DIGITAL TOOL AND METHOD BOX

PERIOD: 2017

GOAL

  • Use smart data to enhance traditional market research
  • Identify new sales stories, trends, and consumer needs based on search data
  • Support content and marketing managers in their decision-making

CHALLENGE

  • Handling the analysis of over 6,500 search terms
  • Automating the smart data approach

SOLUTION

TD Reply helped DekaBank to identify trending marketing content that is relevant to the needs of its existing and prospective customers. Analyzing over 6,500 search terms and applying various algorithmic approaches, TD Reply created consumer-centric sales stories that were highly relevant to the target audience.

Thanks to an easy-access insights dashboard,” DekaBank employees can keep track of current consumer trends based on Google search data. Additional 360-degree trend reporting allows DekaBank to take deep dives into its potential content fields.

The dashboard thus allows DekaBank to monitor the financial needs and business growth of its customers and prospects much more frequently and in greater detail than traditional market research would ever allow.

DATA-DRIVEN BUSINESS TRANSFORMATION

PERIOD: 2015–2016

GOAL

In the process of exploring new and innovative ways to initiate a data-driven transformation process, Döhler has three key objectives:

  • Enhancing the decision-making process through data-driven transparency
  • Improving consumer/customer/competitor intelligence by identifying action fields and opportunities
  • Initiating a data-driven business transformation process by implementing a company-wide smart data solution across the entire value chain

CHALLENGE

  • Understanding and assessing the current smart data readiness and information needs of each department, and the development of a smart data roadmap
  • Exploring new data sources and methods to gain insights and evaluate the business value
  • Gathering and analyzing new data in order to identify growth opportunities and action fields (e.g. data as a service) that can be developed outside of Döhler’s core business for commercialization with partners, customers, etc.

SOLUTION

Market Intelligence Dashboard

The automated dashboard reflects company-specific use cases allowing the comparison of different brand and ingredient KPIs to identify market opportunities and trigger innovations and sales. Furthermore, the dashboard provides cross-cutting approaches that ensure holistic ecosystem-based management, including customer, competitor, sourcing, and processing views. The comprehensive source set includes a wide range of data, including Euromonitor data and Mintel insights, as well as buzz and search data.

FRANCHISE LIFECYCLE MANAGEMENT

PERIOD: 2018

GOAL

Due to the critical role of key franchises for overall commercial success (Top 10 franchises make between 40-70% of overall revenue across the top sportswear brands), adidas wanted to gain deeper insights on how franchises should be managed and tracked along their lifecycles in the market.

Specifically, the client wanted to:

  • Understand Market Mechanics
  • Review Competitor Best Practices
  • Improve Franchise Management

CHALLENGE

As the scope of the analysis was on understanding life cycle mechanics and patterns one key challenge was to gain “long enough” historical timeseries data, especially for key franchises that are at later stages of the life cycle.

Another challenge was to identify success factors and leading indicators for franchises success across brands and categories.

SOLUTION

TD Reply conducted an extensive Research Project analyzing 52 Franchises across 7 Brands in 5 sportswear categories.

Understand: Identification and fitting of franchise curves to statistical distributions, clustering of franchises by distribution parameters and splitting life cycles into stages

Locate: Creating a KPI set with benchmarks based on average stage performance to track franchise performance

Predict: Prediction of life cycle development in terms of the height & length of life cycles and stage entries

Steer: Development of lifecycle & portfolio frameworks (product launches, iterations, activations, …) to advance franchise management & planning

The analysis and modeling were based on around 1 Mio. data points and 17 KPIs including internal client’s data (e.g. article invest, sales and discounts), external market data (e.g. market shares) as well as digital data generated by TD Reply (e.g. google search, social media buzz and franchise image buzz).

Results of the project have been presented to the board and senior management across key business units and are used for portfolio and franchise lifecycle management decisions.

DIGITAL BRAND EQUITY TRACKING

PERIOD: 2018–ONGOING

GOAL

Drive strategy and execution from a brand perspective through a digital brand tracking system that can:

  • Measure the level of brand equity for adidas and competitors in near real-time 
  • Gives insights on how products, assets and campaigns are perceived and how they contribute to the overall brand perception
  • Measure the contribution of the brand to overall marketing success and sales

CHALLENGE

The initial challenge was to translate abstract brand personality and image items that have been tracked through traditional surveys into consumer language that enables us to track and analyze consumer conversations related to the brand drivers on a very granular level (besides overall brand perception we are able to understand how individual franchises, drops, technologies, assets etc. are perceived by consumers).

Another challenge within the project was to drive change and acceptance within the organization. As we know data projects are change projects, thus the internal communication together with the owner on the client side, was and still is a key aspect of the overall project.

SOLUTION

TD Reply developed a new approach to track the brand values of adidas and key competitors by analyzing digital data. The process involved the following steps:

Brand Meaning: Itemization of adidas brand values by translating all brand-relevant dimensions into consumer language and identifying key digital brand drivers.

Brand Performance: Data Gathering and analysis of the Digital Brand Perception for adidas and Competitors on different levels:

  • Brand Level
  • Sport Category Level
  • Franchise / Asset Level
  • Campaign Level

Brand Mechanics: Creation of an Input-Output-Outcome Model to better understand Marketing Cause-and-effect relationships and optimize the allocation of brand assets to maximize brand impact.

The approach was developed and tested in the US as pilot market and is rolled out across markets (Germany, UK, France, Japan, China).

CREATING A DIGITAL SERVICE EXTENSION

PERIOD: 2014–2017

GOAL

  • Build and maintain a community that serves as one-stop shop for professionals in the area of cataracts.
  • Continuously optimize the community with respect to content integration and customer experience optimization.
  • Integrate tools and services to deliver on key benefit: a“one-stop solution” to support users in their daily workflow overall, saving their time, improving outcome through shared expertise and enhanced knowledge, increasing efficiency and practice throughput.

CHALLENGE

  • Continuously integrating services previously launched as silos into the cataract community delivering on the promise of a “one-stop solution”
  • Creating editorial plans together with the product teams to continuously provide new and interesting content based on customer behavior and interests
  • Transforming internal thinking from a product driven company to a service driven company

SOLUTION

TD Reply implemented a modular open innovation platform based on LifeRay. The intention was to provide a wealth of content together with the possibility to ask questions, exchange with colleagues and provide access to experts. Content and page structure are continuously monitored to provide insight on how to improve customer experience and deliver content that meets customers’ interests and needs. Community management connected to specialists within Carl Zeiss Meditec guarantees fast reactions to user questions.

KPI CONCEPT DEVELOPMENT

PERIOD: 2016

GOAL

Our client Sanofi faces three key objectives:

  • Developing an initial KPI concept based on two pilot cases that serves as a global blueprint for Sanofi across markets and business units
  • Identifying data blind spots
  • Making sure the KPI concept serves the following criteria:

  1. Practicability: use only data that is available to Sanofi
  2. Usefulness: support the decision-making of marketing stakeholders
  3. Scalability: ensure roll-out beyond the two defined pilots

CHALLENGE

  • Each channel needed to be evaluated independently – a multi-channel approach was not feasible.
  • Highly diverse products, target groups, and marketing channels made the development of “one KPI concept for all” difficult.
  • There had been no unified reporting so far. This means that stakeholders are making and using decisions based on various data sources.

SOLUTION

  • Development of the KPI concept along a generic funnel from awareness via interest and activation to sales, and, eventually, loyalty.
  • Development of a scores-per-funnel step that makes campaigns comparable – regardless of product category or business unit.
  • Implementation of a “traffic light system” that serves as an early indicator for the success or failure of a campaign or activation.

RESULTS

  • Common understanding of marketing success and multi-channel steering.
  • Development of a means to steer and orchestrate multi-channel activities.
  • Roll-out of the concept within the global Multi-Channel Engagement Program.

USP CO-CREATION 2020 IN THE AUTOMOTIVE INDUSTRY

PERIOD: 2016

GOAL

To stay at the forefront of its segment, SEAT decided to address the needs of a more urban and progressive target group with a new positioning and clear product USPs based on solid research and in-depth consumer insights.

CHALLENGE

One challenge the client had when deciding how to define the USP features for the next Leon was to identify the right methodology. On the one hand, SEAT wanted to base the future product USPs on solid consumer research, especially as it needed to gain in-depth understanding of a new target group. On the other hand, SEAT was skeptical as to whether consumers could come up with new feature ideas and evaluate their importance and uniqueness in 2020.

A further challenge was to involve stakeholders from multiple departments – ranging from market intelligence, innovation management, and research and development to product management – to not only combine their expertise, but also find consensus throughout the process.

SOLUTION

TD Reply’s Data-Driven Innovation Team came up with a multi-method project approach that combined state-of-the-art digital research methods, such as online buzz analysis (scraping and analyzing conversations of consumers in social media) and research communities (asynchronous online focus groups) with design thinking principles and real-life co-creation workshops across Germany, UK, France, Spain, and Italy.

Status quo analysis: Identification of best cases within the mass market and premium segment matching the targeted positioning of the new Leon.

Buzz analysis: In-depth quantitative and qualitative analysis of online conversations in social media around car models and features across EU5 countries to derive the strengths, weaknesses, and potential USP features based on unbiased consumer discussions.

Co-creation workshop: Identification and recruiting of automotive/non-automotive experts and lead users coupled with a co-creation workshop to develop positioning concepts and feature ideas by applying design thinking principles and methods.

Research communities: Validation and enrichment of prioritized USP features and positioning concepts with consumers over the course of one week in asynchronous online focus groups across EU5 markets.

Transition workshop: Synthesis of overall research results and selection of USP features for the launch in 2020 as well as definition of a USP feature roadmap that will inform the product lifecycle strategy.

R&D PETNOGRAPHY RELOADED

PERIOD: 2017 –2018

GOAL

  • Evaluate the feeding habits, expectations and perceptions of modern dog owners
  • Identify requirements for future pet food and new business opportunities
  • Analyze the public perception of Mars Petcare and their key competitors
  • Gain actionable insights for marketing and product development

CHALLENGE

  • Finding the best tool for qualitative and quantitative social media analysis and defining relevant pet food related search queries for all markets
  • Researching relevant online communities, blogs, review sites and social news sites for cat and dog owners in UK, US and China
  • Update and identifying consumer needs, feeding relevant trends and best cases
  • Collecting valuable insights relevant for all three key markets; finding similarities and main differences between the markets
  • Derivation of opportunities for customer-centric innovations
  • Engaging the multinational project team, with team members from TD Reply’s Berlin and Beijing office
  • Transferring the outcome to the relevant stakeholders the study belongs to (from different departments and country markets of Mars Petcare)

SOLUTION

The 3-step process of the netnography enables us to gain emphatic insights from pet owners, to identify new product developments and derive inspiration for the marketing and innovation pipeline of Mars Petcare.

  • Set-up: First, we started with the project set-up, at which we defined relevant social media sources and pet food related search queries, initiated the automated data collection and a manual quality control of the data set.
  • Buzz Analysis: Secondly, we did a quantitative analysis of relevant buzzwords and brands, followed by a qualitative content analysis, the interpretation of consumers’ postings (related to pet owner’s needs, lifestyles and the related purchasing behavior) and the clustering of all insights.
  • Opportunity Mapping: In a third step we developed an opportunity map for Mars Petcare, with 3 main feeding trends, 9 opportunity fields and 20 rising product categories, which we enhanced with detailed descriptions, trend related personas, best cases, country deep dives and brand insights.