I-COM Data Creativity Awards

Award Categories

The I-COM Data Creativity Awards comprises 23 Award categories,
2 Special categories and 1 Overall Winner Award.

Main Categories

Performance Measurement

Category Definition
I-COM defines the Attribution Category as follows:
Rewarding work that measures the incremental value of marketing channels, strategies and tactics against business outcomes. Attribution should directly drive optimization of marketing to improve business outcomes.
Further clarifications include:
• Business outcomes include sales, intermediate metrics to sales and brand metrics
• Marketing channels cover Digital and non-Digital
Category Objective
Align the industry on the definition of attribution. Showcase what is happening at the cutting edge of this space and the positive business impact it is delivering.
Spark discussion of how attribution is changing client businesses and why. Provide case studies for marketers to reference. Drive further application of the science of attribution to encourage meaningful change in the industry.
Judging & Criteria
50% of the scoring based on the actual project results (for example: ROI, Awareness, Degree of Process Improvement).
50% on the extent to which innovative and creative approaches were adopted in achieving those results.
Successful entries will include one or more of the following elements:
A. General Data Creativity Elements
• Creating New Insights from Multiple Data Sources
• Effective and Efficient Integration of Data
• Innovative Data Sourcing
• Analytics Creativity
• Using Insights to Evolve the Planning and Execution Process
• Employing Different Marketing Sciences
• Technology Innovation (in-house or with 3rd parties)
• Innovative Data Visualisation
B. Specific Elements of Attribution
• Data enablement, assembly and management
• Measurement methodology
- Accuracy of results
- Sufficient transparency of approach
• Scope and comprehensiveness of solution
- Level of unknown
- How closely does it match the reality of the client’s business
- User segmentation
• Time to results
- Time from start to meaningful results
• Frequency of results
• Explainability of results
• Actionability of results
• Key decision support (nice to know vs. need to know)
- Repeatability
- Optimization of marketing to improve business outcomes
- Frequency of attribution in line with frequency of actions/course corrections
• Adoption within organization
• Applicability / Portability to the same channel, clients or industries with a different provider
Who Should Enter?
Media Agencies, Creative Agencies, Attribution Providers, Consultancies, In-House Attribution departments in major marketing companies, PurePlay, Market Research, Marketing Tech, Media Owners
Category Definition
Attention refers to the ability of an advertisement to capture and maintain a user's focus and engagement. It is a measure of how much the ad stands out from the other content on the page and how well it holds the viewer's interest.
As the demise of the cookie and restrictions on tracking via mobile devices loom, marketers are compelled to reassess traditional methods of gauging if their ads reached the intended audience.
Effective attention-grabbing ads can help drive traffic to a website, increase brand awareness, and ultimately lead to higher conversions and sales. To achieve this, digital advertisers use a range of techniques, including targeted audience segmentation, personalised messaging, and the use of eye-catching visuals or videos to capture the user's attention.
Category Objective
Provide case studies for companies to reference. Drive further application of new attention metrics approaches to achieve meaningful change in the industry.
Align the industry on the definition of Attention. Showcase what is happening at the cutting edge of this space and the positive business impact it is delivering.
Spark discussion of how Attention is changing client businesses and why, and how to address these challenges
Judging & Criteria
50% of the scoring is based on the actual project results (for example: ROI, Awareness, Degree of Process Improvement).
50% on the extent to which innovative and creative approaches were adopted in achieving those results.
Successful entries will include one or more of the following elements:
A. General Data Creativity Elements
• Creating New Insights From Multiple Data Sources
• Effective and Efficient Integration of Data
• Innovative Data Sourcing
• Analytics Creativity
• Using Insights To Evolve The Planning And Execution Process
• Employing Different Marketing Sciences
• Technology Innovation (in-house or with 3rd parties)
• Innovative Data Visualisation
B. Specific Data Creativity Elements to the Attention Category
• Business Application - Meaningful business application, demonstrating how Attention can drive business outcomes
• Data - The “quality” of Attention data sources applied, robust methodology from sourcing data to measuring outcomes
• Strategy - How is the creative use of Attention data applied strategically within marketing efforts (media and/or creative)
• Measurement - methods employed to determine success and impact on business
• Insights – How have results been aggregated to form findings and what implications and recommendations have enabled decision making
• Innovation – Innovation – How the evolution or application of Attention technology has driven innovation?
Category Definition
I-COM defines the Incrementality Experiments category as follows: This award category aims to highlight professional excellence in the practice of prospective randomized experiments to measure the "incremental" effect of marketing investments on key outcomes, notably sales.
That incremental effect should be measured relative to a randomized control group drawn from the same audience population targeted by the campaign(s) of interest. Techniques for running such advertising experiments include "ghost ads," PSA placebos, intent to treat, and geo-tests.
Experiments in this category stand in contrast to observational methods of estimating effect of advertising, which should be submitted to the Incrementality Inference category instead.
Category Objective
The objective for this category is to help educate the marketing community about best practices in this important emerging field.
Judging & Criteria
50% of the scoring based on the actual project results (for example: ROI, Awareness, Degree of Process Improvement).
50% on the extent to which innovative and creative approaches were adopted in achieving those results.
Successful entries will address one or more of the following elements:
A. General Data Creativity Elements
• Creating New Insights from Multiple Data Sources
• Effective and Efficient Integration of Data
• Innovative Data Sourcing
• Analytics Creativity
• Using Insights to Evolve the Planning and Execution Process
• Employing Different Marketing Sciences
• Technology Innovation (in-house or with 3rd parties)
• Innovative Data Visualisation
B. Elements of Data Creativity specific to the Incrementality Experiments category:
1. Clear business decision to be supported by experiment
1. a. Definition of experiment hypothesis
1. b. Demonstration of Business Application of findings from experiment
2. Experiment Mode
2. a. Intent to Treat
2. b. Geo Experiment
2. c. Ghost Ads / Ghost Bids
2. d. PSA/House Ad Placebo
2. e. Other
3. Randomization Units
3. a. Persons
3. b. Devices (cookies, MAIDs, STB IDs, etc.)
3. c. Account logins
3. d. Households
3. e. Zip codes
3. f. DMAs
3. g. Other
4. Media Spaces
4. a. TV
4. b. OTT / CTV
4. c. Social Media
4. d. Search
4.e Display/Programmatic
4. f. Multiple Media
4. b. Other
5. Outcome Data
5. a. Online Sales
5. b. In-store Sales
5. c. Other
6. Experiment Validation
6. a. Balance Testing (pre-testing for ITT; post-experiment for Ghost Ads/PSAs
6. b. Demonstration of no prior pre-disposition for brand in test or control
6. c. Identity Graph Validation
6. d. A/A testing
6.e Bias analysis (examination of any potential for systemic error in measurement instrument)
6. f. Methods transparency
7. How are the findings projected to the entire universe
7. a. Accounting for biases in the included data
7. b. Accounting for universe-level available data
Who should enter?
Marketers, Agencies, Media companies, Ad-Tech Companies
Category Definition
I-COM defines the Incrementality Inference Category as follows: The Incrementality Inference award recognizes innovation and creativity that enhances the measures of the incremental value of advertising based on models with synthetic controls to improve optimization and business outcomes.
Submissions for this category stand in contrast to prospective experiments methods of measuring effect of advertising, which should be submitted to the Incrementality Experiments category instead.
Category Objective
To showcase the importance of estimating the incremental value of advertising with quasi-experiments, econometric models and similar approaches. This is as opposed to last-click or other methods that do not account for incrementality above the audience's propensity to buy already. This award showcases what is happening at the cutting edge of this space and the positive business impact it is delivering.
Judging & Criteria
50% of the scoring based on the actual project results (for example: ROI, Awareness, Degree of Process Improvement).
50% on the extent to which innovative and creative approaches were adopted in achieving those results.
Successful entries will address one or more of the following elements:
A. General Data Creativity Elements
• Creating New Insights from Multiple Data Sources
• Effective and Efficient Integration of Data
• Innovative Data Sourcing
• Analytics Creativity
• Using Insights to Evolve the Planning and Execution Process
• Employing Different Marketing Sciences
• Technology Innovation (in-house or with 3rd parties)
• Innovative Data Visualisation
B. Elements of Data Creativity specific to the Incrementality Inference category:
1. Method for isolating incrementality
1. a. Methodology employed to separate the impact of targeting from actual incrementality
1. b. Methodology employed to account for propensity to buy or propensity to respond
2. Data included to determine incrementality
2. a. Pre-period purchase or responsiveness data
2. b. Non-pre-period purchase or responsiveness data
3. Tests conducted to ensure Incrementality
3. a. Random control trials, ghost ads, Intent to Treat or other experiments
3. b. Synthetic data
3. c. A/A tests or other tests which measure the effects when exposure is randomly assigned with the expectation of zero incremental lift
4. How are the findings projected to the entire universe
4. a. Accounting for biases in the included data
4. b. Accounting for universe-level available data
Who should enter?
Marketers, Agencies, Media companies, Ad-Tech Companies
Category Definition
I-COM defines the Location Based category as work involving data stemming from mobile devices. The data does not need to be exclusively mobile and can be cross-channel in nature.
Category Objective
The objective of the Location Based category is to reward projects that capture the unique value and overcome the challenges, stemming from mobile device usage. Examples include creative use of Proximity generated insights, Geo-location data, Innovation in Retail, Telecom, etc.
Judging & Criteria
50% of the scoring based on the actual project results (for example: ROI, Awareness, Degree of Process Improvement).
50% on the extent to which innovative and creative approaches were adopted in achieving those results.
Successful entries will address one or more of the following elements:
A. General Data Creativity Elements
• Creating New Insights from Multiple Data Sources
• Effective and Efficient Integration of Data
• Innovative Data Sourcing
• Analytics Creativity
• Using Insights to Evolve the Planning and Execution Process
• Employing Different Marketing Sciences
• Technology Innovation (in-house or with 3rd parties)
• Innovative Data Visualisation
B. Specific Data Creativity Elements
Demonstrate the unique value and overcome the challenges, stemming from mobile device usage
Who Should Enter?
All parties involved in Location Based communications, such as Mobile and Digital Agencies, Advertising Agencies, PR Agencies, Marketers, Media Owners, Brands, etc.

Marketing Sciences

Category Definition
I-COM defines the Artificial Intelligence Category as follows:
Artificial Intelligence is regarded as a computerised system that exhibits behaviour that is commonly thought of as requiring intelligence. AI problems and solutions fall into one of the following categories:
• Systems that think like humans (e.g., cognitive architectures and neural networks);
• Systems that act like humans (e.g., pass the Turing test via natural language processing; knowledge representation, automated reasoning, and learning),
• Systems that think rationally (e.g., logic solvers, inference, and optimization); and
• Systems that act rationally (e.g., intelligent software agents and embodied robots that achieve goals via perception, planning, reasoning, learning, communicating, decision-making, and acting).
Category Objective
Align the industry on the definition of Artificial Intelligence. Showcase what is happening on the cutting edge of this space and the positive business impact it is delivering.
Spark discussion of how Artificial Intelligence is changing client businesses and why. Provide case studies for marketers to reference. Drive further application of the science of Artificial Intelligence to encourage meaningful change in the industry.
Judging & Criteria
50% of the scoring based on the actual project results (for example: ROI, Awareness, Degree of Process Improvement)
50% to the extent to which Data Creativity in Artificial Intelligence was adopted in achieving those results.
Successful entries will address one or more of the following elements:
A. General Data Creativity Elements
• Creating New Insights From Multiple Data Sources
• Effective and Efficient Integration of Data
• Innovative Data Sourcing
• Analytics Creativity
• Using Insights to Evolve the Planning and Execution Process
• Employing Different Marketing Sciences
• Technology Innovation (in-house or with 3rd parties)
• Innovative Data Visualisation
B. Elements of Data Creativity Specific to the Artificial Intelligence Category
1. Business Application
• Meaningful business application that is very difficult (if not impossible) for human beings to achieve, producing consistent and efficient business outcomes
• Perform functions in one or more of the 4 categories mentioned on the definition
2. Data
• AI systems typically deal with Big Data to generate and validate intelligence; however, the Big Data can be openly available for training purposes and not necessarily proprietary to the business. Innovative uses of open-source data sets to help with achieving business objectives are accepted
• AI system involves one or multiple forms of data - numeric, image, text, audio, video, etc.
3. System Implementation
• The final AI system needs to be nearly automated with limited human interaction
• Main methods deployed in the AI system should be cutting-edge machine learning techniques, not traditional rule-based programming
Who Should Enter?
Advertising Agencies, Ad Tech/Marketing Tech companies, Big Data companies, Brands/Brand Owners, Consultancies, Universities
Category Definition
I-COM defines the Behavioural Science category as work that reflects an achievement in understanding, motivating or optimizing behavioural response through the application of pre-intended Behavioural Science constructs among target groups such as consumers, customers voters or B2B targets based on understanding human behaviour and its drivers.
Qualifying entries must include data stemming from the evaluation of data sets and/or new or alternative treatments and scenarios based upon potential marketing influencers such as communications, media, pricing or product features demonstrating that outcomes have been better understood, evoked and/or measured for behavioural impact.
Category Objective
The objective of this category is to encourage and recognize creativity in applying scientific insights and methods stemming from the multidisciplinary field of Behavioural Science including Behavioural Economics, Neuroscience, Cognitive Psychology and Anthropology, to find innovative ways of understanding, motivating and/or affecting behaviour among defined target groups for media and marketers.
This can take many forms including behavioural science-driven data analytics, experimental design with concepts or scenarios which establish that through the application of one or more constructs of Behavioural Science, human behaviour can be positively impacted.
Judging & Criteria
50% of the scoring is based on the actual project results (for example: ROI, Attention, Response Rates, Purchase Incidence, Change in Repeat Purchase, etc.)
50% to the extent to which Data Creativity in Behavioral Science was applied in achieving those results.
Successful entries will address one or more of the following elements:
A. General Data Creativity Elements
• Creating New Insights from Multiple Data Sources
• Effective and Efficient Integration of Data
• Innovative Data Sourcing
• Analytics Creativity
• Using Insights to Evolve the Planning and Execution Process
• Employing Different Marketing Sciences
• Technology Innovation (in-house or with 3rd parties)
• Innovative Data Visualisation
B. Elements of Data Creativity specific to the Application of Behavioural Science Constructs can include outcomes such as:
• Behavioural approaches which create, increase or explain response among target audiences: Increased viewership, response rates, inquiries, purchases, usage, etc.
• Increased viewership, response rates, inquiries, purchases, usage, etc.
• Creating an understanding of conscious and non-conscious choice drivers
• Designing and enabling enhanced UX experiences
• Design research practices to generate behavioural-driven consumer insights
• Establishing ways to build better models incorporating Behavioural Science data, eliminating psychological biases in our interpretations, and developing a deeper understanding of the psychology of consumers and customers.
Who should enter?
Marketers, Advertising / Communications Agencies, Behavioural Science / Neuro / Research Companies / Consultancies, Academics, Media Platforms, Networks, Social Media Platforms
Category Definition
Creative Automation is a digital marketing and advertising strategy that involves using technology and automation tools to streamline and optimise the process of creating, customising, and delivering creative content for advertising campaigns.

It aims to improve efficiency and effectiveness, as well as cost reduction in the creative aspects of marketing by reducing manual labour and repetitive tasks while maintaining or even enhancing the quality of creative materials.

Category Objective
Provide case studies for companies to reference. Drive further application of improvement on key elements of Creative Automation and approaches to achieve meaningful change in the industry.
Align the industry on the definition of Creative Automation. Showcase what is happening at the cutting edge of this space and the positive business impact it is delivering.
Spark discussion of how innovation in Creative Automation is changing client businesses and why, and how to address these challenges.

Judging & Criteria
50% of the scoring based on the actual project results (for example: ROI, Awareness, Degree of Process Improvement)
50% to the extent to which Data Creativity in Creative Automation was adopted in achieving those results.

Successful entries will address one or more of the following elements:

A. General Data Creativity Elements

• Creating New Insights From Multiple Data Sources
• Effective and Efficient Integration of Data
• Innovative Data Sourcing
• Analytics Creativity
• Using Insights to Evolve the Planning and Execution Process
• Employing Different Marketing Sciences
• Technology Innovation (in-house or with 3rd parties)
• Innovative Data Visualisation

B. Elements of Data Creativity Specific to the Creative Automation Category

• Dynamic ad generation, based on user data or behaviour
• Automatic generation of multiple versions of an ad by filling in variable elements, ensuring consistent branding while allowing for customization.
• A/B testing of various creative elements, such as headlines, images, or calls to action.
• Multi-Channel Adaptation
• Data Integration

Who Should Enter?
Advertising Agencies, Ad Tech/Marketing Tech companies, Big Data companies, Brands, Consultancies, Technology suppliers
Category Definition
I-COM defines the Data Visualisation category as work that efficiently conveys a complex data set in a meaningful, scannable way that leads to business impact.
Category Objective
We are highlighting the value of great data visualisation by honoring companies that are applying data visualisation in unique ways that we can all learn from.
Entrants will show that they began with a complex data set, presented it in a visual that is easy to scan and intuitively draw deductions from and enabled a decision to be made.
Judging & Criteria
50% of the scoring based on the actual project results (for example: ROI, Awareness, Degree of Process Improvement).
50% on the extent to which innovative and creative approaches were adopted in achieving those results.
Successful entries will address one or more of the following elements:
A. General Data Creativity Elements
• Creating New Insights from Multiple Data Sources
• Effective and Efficient Integration of Data
• Innovative Data Sourcing
• Analytics Creativity
• Using Insights to Evolve the Planning and Execution Process
• Employing Different Marketing Sciences
• Technology Innovation (in-house or with 3rd parties)
• Innovative Data Visualisation
B. Elements of Data Creativity Specific to the Data Visualisation Category:
• Relevance – delivering intellectual and emotional impact to the right audience
• Consequence - illuminating one or more paths ahead
• Action – Changing or affirming a behaviour or decision for which there are credible options
• Measurement – quantifying the impact
• Replicable - can be applied to a broad set of real life applications, cross-platform
• Immediacy - the ability to react in the moment, when action can still be taken, rather than just reviewing afterwards
• Simplicity – without losing clarity
• Design Quality - appealing and intuitively comprehensible
• Innovative and Creative – New and unique
• Accurate - truly representative of the underlying data, mathematical truth
Who Should Enter?
Companies involved in visualising marketing data, including Data Scientists, User Interface Designers and Marketing Executives drawn from Marketers, Digital Agencies, Design Firms, Media Owners or Research Houses.
Category Definition
Generative AI refers to a class of artificial intelligence systems that are designed to generate new content, such as images, video, text, or even audio, that is similar to or inspired by existing data. These systems use various techniques, including LLMs, to create this content.

Generative AI has several valuable applications in digital marketing, helping businesses improve their marketing strategies, personalise content, and engage with customers more effectively.

Category Objective
• Align the industry on the definition of Generative Artificial Intelligence.
• Showcase what is happening on the cutting edge of this space and the positive business impact it is delivering.
• Spark discussion of how Generative Artificial Intelligence are changing client businesses and why. Provide case studies for marketers to reference.
• Drive further application of Generative Artificial Intelligence to encourage meaningful change in the industry.

Judging & Criteria
50% of the scoring based on the actual project results (for example: ROI, Awareness, Degree of Process Improvement)
50% to the extent to which Data Creativity in Generative Artificial Intelligence was adopted in achieving those results.

Successful entries will address one or more of the following elements:

A. General Data Creativity Elements
• Creating New Insights From Multiple Data Sources
• Effective and Efficient Integration of Data
• Innovative Data Sourcing
• Analytics Creativity
• Using Insights to Evolve the Planning and Execution Process
• Employing Different Marketing Sciences
• Technology Innovation (in-house or with 3rd parties)
• Innovative Data Visualisation

B. Elements of Data Creativity Specific to the Gen AI Category
Usage of Gen AI to provide solutions to business problems that lead to consistent results in:
• Creative production or enhancement, including full writing tasks (copy, blog posts, ads, etc)
• Enhancing the efficiency of office work, such as data analytics, pattern and anomaly detection within sets of data.
• Media performance storytelling: has the use of Generative AI enabled the effective summarization and storytelling of the performance of media (paid, earned and owned)?
Who Should Enter?
Advertising Agencies, Ad Tech/Marketing Tech companies, Big Data companies, Brands, Consultancies, AI technology suppliers, Others
Category Definition
I-COM defines the General category as any work that broadly covers and shows evidence of the creative leveraging of value from data that is instrumental to delivering business value.
Category Objective
The objective of the General category is to acknowledge the most creative people and companies in achieving business value and ideally competitive advantage for their clients by leveraging value from data.
Judging & Criteria
50% of the scoring based on the actual project results (for example: ROI, Awareness, Degree of Process Improvement).
50% on the extent to which innovative and creative approaches were adopted in achieving those results.
Successful entries will include one or more of the following elements:
A. General Data Creativity Elements
• Creating New Insights from Multiple Data Sources
• Effective and Efficient Integration of Data
• Innovative Data Sourcing
• Analytics Creativity
• Using Insights to Evolve the Planning and Execution Process
• Employing Different Marketing Sciences
• Technology Innovation (in-house or with 3rd parties)
• Innovative Data Visualisation
Who Should Enter?
Marketers, Creative Agencies, Media Agencies, Media Owners, Data Services/Research Providers and Trade Associations involved in digital marketing.

Customer Centric

Category Definition
I-COM defines the Content Marketing category as follows:
Rewarding work that involves a strategic and tactical marketing approach focused on creating and distributing information to the buyer that is valuable, relevant and helpful for a target audience using a combination of owned media (e.g. blogs, micro-sites, social media conversations, print and digital publications, etc.), paid media and earned media.
Category Objective
To showcase what is happening in the creative application of data in this space and the positive business impact delivered.
Align the industry on the definition of Content Marketing. Spark a discussion of how Content Marketing is changing communication strategy and tactics. Provide case studies for marketers to reference. Drive further application of Content Marketing to effect meaningful change in the industry.
Judging & Criteria
50% of the scoring based on the actual project results (for example: ROI, Awareness, Degree of Process Improvement).
50% to the extent to which Data Creativity in Content Marketing was adopted in achieving those results.
Successful entries will include one or more of the following elements:
A. General Data Creativity Elements
• Creating New Insights from Multiple Data Sources
• Effective and Efficient Integration of Data
• Innovative Data Sourcing
• Analytics Creativity
• Using Insights to Evolve the Planning and Execution Process
• Employing Different Marketing Sciences
• Technology Innovation (in-house or with 3rd parties)
• Innovative Data Visualisation
B. Elements of Data Creativity Specific to the Content Marketing Category
• Data enablement, assembly and management
• Ability to adapt to emerging data signals
• Measurement methodology
• Accuracy of results
• Sufficient transparency of approach
• Scope and comprehensiveness of solution
• Level of unknown
• How closely does it match the reality of client’s business
• User segmentation
• Time to results
• Time from start to meaningful results
• Illustration of the value of content marketing to their organization
• Actionability of results
• Key decision support (nice to know vs. need to know)
• Repeatability
• Optimisation of content marketing to improve business outcomes
• Utilisation of feedback loop
Who Should Enter?
Media, Creative Agencies, Media Agencies, Marketers, Solution providers - Platforms (e.g. Vice, Spotify, Contently, Buzzfeed, StoryFull, Mashable, Adobe)
Category Definition
I-COM defines the CRM Category as follows:
Rewarding work that leverages known customer data to better drive and measure marketing results across all channels.
Category Objective
Recognize massive merging between media and CRM business, convergence.
Judging & Criteria
50% of the scoring based on the actual project results (for example: ROI, Awareness, Degree of Process Improvement).
50% on the extent to which innovative and creative approaches were adopted in achieving those results.
Successful entries will include one or more of the following elements:
A. General Data Creativity Elements
• Creating New Insights from Multiple Data Sources
• Effective and Efficient Integration of Data
• Innovative Data Sourcing
• Analytics Creativity
• Using Insights to Evolve the Planning and Execution Process
• Employing Different Marketing Sciences
• Technology Innovation (in-house or with 3rd parties)
• Innovative Data Visualisation
B. Elements of Data Creativity Specific to the CRM Category
• Degree of Applicability across multiple devices, channels, geographies or ad formats
• Scalability
• Unique use of disparate data sets
• Innovation in managing identity (must maintain PII)
Who Should Enter?
Companies with a CRM file, Retailers, companies that are in the Media Space, Television Networks, AdTech companies, Agencies, CRM Software companies.
Category Definition
Customer Experience (CX) is a holistic and multifaceted concept that encompasses all interactions and touchpoints a customer has with a brand, product, or service throughout their entire journey, from initial awareness and consideration to purchase, usage, post-purchase and ownership support.

It represents the sum total of a customer's perceptions, feelings, and opinions about their interactions and overall relationship with a business.

Category Objective
• Provide case studies for companies to reference. Drive further application of improvement on key elements of Customer Experience to achieve meaningful change in the industry.
• Align the industry on the definition of Customer Experience. Showcase what is happening at the cutting edge of this space and the positive business impact it is delivering.
• Spark discussion of how innovation in Customer Experience approaches is changing client businesses and why, and how to address these challenges.

Judging & Criteria
50% of the scoring based on the actual project results (for example: ROI, Awareness, Degree of Process Improvement)
50% to the extent to which Data Creativity in Customer Experience was adopted in achieving those results.

Successful entries will address one or more of the following elements:

A. General Data Creativity Elements
• Creating New Insights From Multiple Data Sources
• Effective and Efficient Integration of Data
• Innovative Data Sourcing
• Analytics Creativity
• Using Insights to Evolve the Planning and Execution Process
• Employing Different Marketing Sciences
• Technology Innovation (in-house or with 3rd parties)
• Innovative Data Visualisation

B. Elements of Data Creativity Specific to the Customer Experience Category
• Customer Feedback and Satisfaction:
◦ Analyse customer feedback through surveys, reviews, and social media comments to gauge overall satisfaction.
◦ Look for trends in customer sentiment to identify areas of improvement or success.
◦ Consider metrics like Net Promoter Score (NPS), Customer Satisfaction (CSAT), and Customer Effort Score (CES).
• Customer Engagement:
◦ Measure the level of customer engagement with campaign content and touchpoints.
◦ Evaluate click-through rates, open rates, and interaction metrics (likes, shares, comments) on social media or email campaigns.
◦ Assess the duration and depth of website visits and interactions.
• Conversion Rates:
◦ Analyze how the campaign has impacted conversion rates, whether it's sales, lead generation, or another specific goal.
◦ Compare conversion rates during the campaign to baseline or historical data.
• Personalization and Targeting:
◦ Evaluate the effectiveness of personalization efforts in the campaign. Are messages and content tailored to individual preferences?
◦ Assess the accuracy of audience segmentation and targeting.
• User Experience (UX):
◦ Consider the ease of navigation and usability of digital assets such as websites, apps, and landing pages.
◦ Evaluate load times, mobile responsiveness, and overall design.
• Consistency Across Channels:
◦ Ensure that the CX is consistent across all digital channels and touchpoints in the customer journey.
◦ Evaluate how well the campaign maintains a unified brand message and identity.
• Customer Journey Mapping:
◦ Review customer journey maps to understand how the campaign aligns with and enhances various stages of the customer journey.
◦ Identify areas where the campaign can improve the overall experience at different touchpoints.
• Customer Retention and Loyalty:
◦ Assess the impact of the campaign on customer retention rates.
◦ Determine if the campaign has contributed to increased customer loyalty or repeat business.
• Data and Analytics:
◦ Utilise data analytics to track key performance indicators (KPIs) related to CX.
◦ Leverage advanced analytics to uncover insights and correlations in customer data.
• ROI and Cost-Effectiveness:
◦ Evaluate the return on investment (ROI) of the campaign, considering both short-term and long-term effects on CX.
◦ Assess the cost-effectiveness of CX improvements in terms of acquisition, retention, and customer lifetime value.
• Competitive Benchmarking:
◦ Compare the campaign's CX metrics to those of competitors to identify areas of relative strength or weakness.
◦ Benchmark against industry standards and best practices.
• Adaptability and Continuous Improvement:
◦ Assess the campaign's ability to adapt to changing customer preferences and market conditions.
◦ Identify areas for continuous improvement in CX based on ongoing feedback and data analysis.
• Employee Engagement:
◦ Consider how the role of employees is an enabler or accelerant in delivering the CX and evaluate their training, motivation, and impact on customer interactions.
Category Definition
I-COM defines this category as the application of privacy-preserving identity solutions, both deterministic and probabilistic, which foster collaboration, drive activation, and improve measurement, in order to achieve one or more of the following outcomes:
• Reaching the intended audience across channels (B2C or B2B)
• Pulling valuable insights which lead to improved results for planning
• Improvement in the ability to enhance measurement to obtain better outcomes.
• Improvement in the ability to safeguard 1st party data
• Improvement in the ability to optimize media spend
• Ability to enhance customer engagement
• Improved time to market
• Ability to increase conversion on site, in-app and/or instore
• Ability to improve the customer/prospect experience (frequency capping)
• Improvement in the ability to connect, enrich and extend 1st party data.
Category Objective
• Showcase diverse approaches on the cutting edge of identity solutions in a changing addressable landscape, and the positive business impact it is delivering.
• Provide case studies for companies to reference. Drive further application of identity solution approaches to achieve meaningful change in the industry.
• Improve identity solutions in a changing regulatory environment and consumer expectations for data privacy.
Judging & Criteria
50% of the scoring based on the actual project results (for example: ROI, Awareness, Degree of Process Improvement).
50% on the extent to which innovative and creative approaches were adopted in achieving those results.
Successful entries will address one or more of the following elements:
A. General Data Creativity Elements
• Creating New Insights from Multiple Data Sources
• Effective and Efficient Integration of Data
• Innovative Data Sourcing
• Analytics Creativity
• Using Insights to Evolve the Planning and Execution Process
• Employing Different Marketing Sciences
• Technology Innovation (in-house or with 3rd parties)
• Innovative Data Visualisation
B. In a changing addressable landscape, that leverages identity solutions, please demonstrate the value your submission has created through improvements in one or multiple areas:
• Targeting quality and the ability to scale.
• Measurement effectiveness
• Insights and planning
• Campaign performance KPIs and/or ROI
• 2nd party data collaboration
• On site personalisation
• Enhancement of Data security/reduction of leakage
• Customer experience
Who should enter?
• Agencies and Consultancies
• Marketers
• Advertising and Marketing Technology companies
• Data/Data Services Providers
• Media companies
Category Definition:
Selected Metaverse Definitions:
• A virtual reality space in which users can interact with a computer-generated environment and other users.
• The metaverse is a vision of what many in the computer industry believe is the next iteration of the internet: a single, shared, immersive, persistent, 3D virtual space where humans experience life in ways they could not in the physical world.
• A network of 3D virtual worlds focused on social connection.
• The metaverse is a continuum of experiences ranging from a 2D video to AR, to entirely immersive 3D VR worlds, all stitched together to form the next iteration of the internet.
In the metaverse, brands create immersive experiences in which their products and services may mirror their forms and functions in the physical world, or take on entirely new shapes, voices, and roles which would only be possible in a virtual world.
Brand activations in the metaverse may introduce the brand to new audiences, strengthen existing connections, or experiment with new models or interaction and service delivery.
Category Objective
To highlight emerging applications of data in the metaverse, including the powering of experiences, measurement of brand effectiveness, and collection of data on interactions and transactions in any immersive platform (AR VR, MR).
Judging & Criteria
50% of the scoring is based on the actual project results (for example: ROI, Awareness, Degree of Process Improvement).
50% on the extent to which innovative and creative approaches were adopted in achieving those results.
Successful entries will include one or more of the following elements:
A. General Data Creativity Elements:
• Creating New Insights from Multiple Data Sources
• Effective and Efficient Integration of Data
• Innovative Data Sourcing
• Analytics Creativity
• Using Insights to Evolve the Planning and Execution Process
• Employing Different Marketing Sciences
• Technology Innovation (in-house or with 3rd parties)
• Innovative Data Visualisation.
B. Specific Data Creativity Elements to the Metaverse Category
• Utilization of the full potential of the platform, technically or experientially
• Taking the brand to new places or new audiences impossible or unavailable in the physical world
• Integration or extension of core functions of the business – ie. does it provide value to prospects and customers, revenue generation via virtual or physical goods, or social impact
• News coverage, social amplification, or other recognition of the activation outside the metaverse.
Category Definition
I-COM defines this category as follows: Rewarding work based on commercial and marketing activities financed by a brand in relation to its online and offline distributors to develop its visibility and sales, leveraging a data-driven approach.
Category Objective
To reward innovation in Targeting, Insights, Media activation and/or Measurement leveraging Retailers' data.
Judging & Criteria
Judging will be based on how innovative and impactful the use case was for the brand leveraging the retailer's data.
50% of the scoring will be based on the actual KPIs of the project: Sales Lift, Incremental ROI, Conversion Rate, Brand awareness, high-quality 1st party data enrichment.
50% on the extent to which innovative and creative approaches were adopted in achieving those results.
Successful entries will address one or more of the following elements:
A. General Data Creativity Elements
• Creating New Insights from Multiple Data Sources
• Effective and Efficient Integration of Data
• Innovative Data Sourcing
• Analytics Creativity
• Using Insights to Evolve the Planning and Execution Process
• Employing Different Marketing Sciences
• Technology Innovation (in-house or with 3rd parties)
• Innovative Data Visualisation
B. Elements of Data Creativity Specific to the Retail Media Category:
• Innovative Targeting.
• Cross Category Usage.
• Scoring Algorithms.
• Uplift Modelling.
• Personalization Strategies.
• Frequency Experimentation.
• Ghost Ads Leveraging Retailer's Data
• Clv Calculation
• Clv Based Programmatic Activation
• Multi Retailer Measurement
• Incrementality Experiments
• Clean Room Experiments
• 1st Party Data Matching
• Audience Validation
Who should enter?
We encourage all companies involved in Retail Media, including but not limited to Digital & Media Agencies, CRM & Loyalty Agencies, Shopper Marketing Agencies, Trading desks, Retail Media Networks, Clean Room providers, Technology providers, Retailers, Media owners, Brands, Research Labs, or a combination of the above.
Category Definition
Total Video is a digital advertising strategy that aims to create a cohesive video experience across all devices and platforms. It involves the use of a variety of video formats, such as pre-roll, mid-roll, out-stream, and in-banner videos, to deliver an integrated video ad campaign that reaches consumers wherever they are consuming content.
Total Video combines the power of TV-style storytelling with the precision targeting and measurement capabilities of digital advertising, making it an effective way for brands to engage audiences and achieve their marketing objectives.
Total Video typically includes both brand-focused and performance-focused video ads, allowing brands to connect with consumers throughout the entire customer journey.
Category Objective
Provide case studies for companies to reference. Drive further application of new approaches to achieve meaningful change in the industry.
Align the industry on the definition of Total Video. Showcase what is happening at the cutting edge of this space and the positive business impact it is delivering.
Spark discussion about the challenges in this space of the industry and how to address them.
Learn what creative solutions to identify fragmentation are available to ensure the provision of a seamless relevant video experience.
Judging & Criteria
50% of the scoring is based on the actual project results (for example: ROI, Awareness, Degree of Process Improvement).
50% on the extent to which innovative and creative approaches were adopted in achieving those results.
Successful entries will include one or more of the following elements:
A. General Data Creativity Elements
• Creating New Insights From Multiple Data Sources
• Effective and Efficient Integration of Data
• Innovative Data Sourcing
• Analytics Creativity
• Using Insights To Evolve The Planning And Execution Process
• Employing Different Marketing Sciences
• Technology Innovation (in-house or with 3rd parties)
• Innovative Data Visualisation
B. Specific Data Creativity Elements to Total Video
• Relevance - Which Identifiers are used to maintain the relevance of ads served through all things video (CTV, OTT, ATV etc.)
• Business Application - Meaningful business application, demonstrating how a Total Video approach can drive business outcomes
• Data - The “quality” of data sources applied, robust methodology from sourcing data to measuring outcomes
• Strategy - How is the creative use of data applied strategically within marketing efforts (media and/or creative)
• Measurement - methods employed to determine success and impact on business
• Insights – How have results been aggregated to form findings and what implications and recommendations have enabled decision making
• Innovation – How the evolution or application of Total Video technology has driven innovation
• Creative approaches - Such as Interactive Video, Personalized Video, User-Generated Content, Storytelling, and integration with other channels.

Organisation Centric

Category Definition
We define Purpose as the strategic intersection between what a business does, how it behaves internally, and the long-term impact it has on people and the planet.
This category rewards the creative use of data/tech which drives actionable outcomes to inspire positive transformative change in society while unlocking new possibilities for growth and value creation, which can be measured beyond commercial success.
Category Objective
Encourage the ethical application of data creation and work which leads to the removal of cultural, systemic or institutional barriers to people's lives, health, safety and wellbeing.
Provide case studies for companies to reference and be inspired.
Drive further application and creation of data to achieve meaningful change in the industry.
Judging & Criteria
50% of the scoring is based on the actual project results (for example: ROI, Attention, Response Rates, Purchase Incidence, Change in Repeat Purchase, etc.)
50% to the extent to which Data Creativity in Behavioral Science was applied in achieving those results.
Successful entries will address one or more of the following elements:
A. General Data Creativity Elements
• Creating New Insights from Multiple Data Sources
• Effective and Efficient Integration of Data
• Innovative Data Sourcing
• Analytics Creativity
• Using Insights to Evolve the Planning and Execution Process
• Employing Different Marketing Sciences
• Technology Innovation (in-house or with 3rd parties)
• Innovative Data Visualisation
B. Elements of Data Creativity specific to the Purpose category:
• Successful entries will include one or more of the following elements:
• The Strategy - How solid is the idea, building research rigour, fit with brand (25%)
• What is the creative use of data/tech on the idea (25%)
• How does that creative use of data/tech drive actionable outcomes (50%), which can be of different natures:
- Commercial
- Societal/Environmental
- Employees and Policies
- People/Consumers
- Data Ecosystem impact – creation of data that is fair, ethical, transparent, diverse, and/or actionable for marketing purposes.
- Partnerships – Activation
Who should enter?
• Marketers
• Advertising/Communication Agencies
• Behavioural Science/Neuro/Research Companies and Consultancies
• Academics
• Media platforms, Networks, Social Media Platforms
• PR Agencies
• Non-Profit Organisations
• Government Agencies
Category Definition
I-COM defines the Data Driven Business Transformation Category as follows:
Rewarding work that utilizes data in a strategic and creative way leading to measurable business transformation results in:
• Change in core business process
• Improved revenue
• Improved margin performance
• Improved time to market
• Category growth
• Increased market share
• Improved operational cost efficiency
*The above list is not exclusive. All entries must be non media-related cases.
Category Objective
Align the industry on the definition of Data Driven Business Transformation. Showcase what is happening on the cutting edge of this space and the positive business impact it is delivering.
Spark discussion of how Data Driven Business Transformation is changing client businesses and why. Provide case studies for companies to reference. Drive further application of Data Driven Business Transformation to encourage meaningful change in the industry.
Judging & Criteria
50% of the scoring based on the actual project results (for example: ROI, Awareness, Degree of Process Improvement).
50% to the extent to which Data Creativity in Data Driven Business Transformation was adopted in achieving those results.
Successful entries will include one or more of the following elements:
A. General Data Creativity Elements
• Creating New Insights from Multiple Data Sources
• Effective and Efficient Integration of Data
• Innovative Data Sourcing
• Analytics Creativity
• Using Insights to Evolve the Planning and Execution Process
• Employing Different Marketing Sciences
• Technology Innovation (in-house or with 3rd parties)
• Innovative Data Visualisation
B. Elements of Data Creativity Specific to the Data Driven Business Transformation Category
1. Scope and comprehensiveness of the transformation
• Full operational transformation of the business
• Affecting only a part of the business process
2. Transformational design
• Data Analysis
• New products developed
3. Time to results
• Time from start to meaningful results
4. Measurable Outcomes
• Improved revenue
• Improved margin performance
• Improved time to market
• Category growth
• Increased market share
• Improved operational cost efficiency
5. Actionability of results
6. Adoption within organization
7. Applicability / Portability to other business processes, similar clients or industries
Who Should Enter?
All kinds of suppliers: service-oriented, software providers and others. Any type of client. All major agencies as well as all ad-tech/mar-tech analytics vendors.
Category Definition
I-COM defines Data Ethics as follows: Data Ethics is both commitment and corresponding operational practices to ensure that data is used legally, justly and fairly and that risk is managed for all stakeholders:
Considerations – Does the company have:
• Commitment to ethical use of data with operational policies to protect data and govern use?
• Mechanisms to put those policies into effect?
• Internal monitoring to ensure mechanisms work?
• Individual participation for people including meaningful transparency and effective controls for people to express their rights and choices?
• Ready to demonstrate operational accountability on request, and remediate where necessary?
Category Objective
Align the industry on the definition of Data Ethics. Showcase how improvements in Data Ethics build and protect trust in marketing.
Spark discussion of how businesses are working to improve Data Ethics and why. Provide case studies for marketers to reference. Make the industry aware of the foundational importance of Data Ethics, on which every data-driven endeavour depends.
Judging & Criteria
40% based upon foundations of a data ethics program: written commitment in the form of policies and processes that speak to data governance and the ethical use of data
40% based upon operational data governance mechanisms that implement commitments and demonstrate ethical use of data, individual rights, and other aspects of Data Ethics
20% maturity of the program, including administrative and technical controls, and other demonstrable accountability aspects
Successful entries will address one or more of the following elements:
A. General Data Creativity Elements
• Creating New Insights from Multiple Data Sources
• Effective and Efficient Integration of Data
• Innovative Data Sourcing
• Analytics Creativity
• Using Insights to Evolve the Planning and Execution Process
• Employing Different Marketing Sciences
• Technology Innovation (in-house or with 3rd parties)
• Innovative Data Visualisation
B. Elements of Data Creativity Specific to the Data Ethics Category
• How does the organisation demonstrate its Commitment to Data Ethics? What policies articulate the organization’s commitments to data ethics?
• What Mechanisms does the organisation have to put those policies into effect?
• How does the organisation conduct internal monitoring to ensure mechanisms work?
• How does the organisation provide individuals with the ability to participate in data use, including meaningful transparency and effective controls for people to express their rights and choices?
• Is the organisation ready to demonstrate operational accountability on request, and remediate where necessary? How is this evidenced?
Who should enter?
• Any and every company that is trying to leverage data in their business, including but not limited to:
• Advertising & Marketing Technology companies
• Agencies & Consultancies
• Brands across all industries
• Data/Data Services Providers
• Marketers
• Media companies
• Universities & Scientific Organisations
• Anyone else not mentioned above!
Category Definition
I-COM defines Data Quality as follows: Data is considered to be of the highest quality if it is optimally suited for its intended purpose. Considerations generally revolve around questions of:
• How accurate is the data?
• How complete is the data?
• Is the data accessible and usable?
• How consistent is the data?
• How useful is the data?
Category Objective
Align the industry on the definition of Data Quality. Showcase how improvements in Data Quality have brought about positive business impacts.
Spark discussion of how businesses are working to improve Data Quality and why. Provide case studies for marketers to reference. Make the industry aware of the foundational importance of Data Quality, on which every data-driven endeavour depends.
Judging & Criteria
40% based upon improvements in data quality, such as data accuracy, completeness, comprehensiveness, usability and consistency.
40% based upon improvements in the usefulness of the data resulting in some positive, measurable outcome.
20% on the extent to which innovative and creative approaches were adopted in achieving those results.
Successful entries will address one or more of the following elements:
A. General Data Creativity Elements
• Creating New Insights from Multiple Data Sources
• Effective and Efficient Integration of Data
• Innovative Data Sourcing
• Analytics Creativity
• Using Insights to Evolve the Planning and Execution Process
• Employing Different Marketing Sciences
• Technology Innovation (in-house or with 3rd parties)
• Innovative Data Visualisation
B. Elements of Data Creativity Specific to the Data Quality Category
• Accuracy
• How is accuracy being measured? How correct are the data and is the tradeoff between accuracy and scale being properly addressed, as appropriate? Are data elements correctly and consistently associated with entities?
• Business Enablement
• What business processes have been implemented to apply improvements across the organization?
• Business Impact
• How have improvements in data quality positively influenced analytics, business decisions, customer relations, organizational efficiency, profitability, and/or revenue?
• Comprehensiveness
Does the data have the elements needed and are they sufficiently granular?
• Consistency
• Is the data consistent across different data stores?
• Conformant
• Is the data stored in a standardized and useful format?
• Flexibility
• Can additional entities or elements (or even data stores) be easily added as needed?
• Harmony
• Is the data well organized and defined as well as easy to navigate?
• Predictive power (efficacy)
• Does the data correlate with, create actionable outcomes for, or provide insight into primary use cases?
• Scale & fill rates
• Is the data set sufficiently large enough to achieve desired outcomes?
• Timeliness
• Is the data sufficiently up to date? Is the tradeoff between timeliness and consistency over time being properly addressed?
Who should enter?
Any and every company that is trying to leverage data in their business, including but not limited to:
• Advertising & Marketing Technology companies
• Agencies & Consultancies
• Brands across all industries
• Data/Data Services Providers
• Marketers
• Media companies
• Universities & Scientific Organizations
• Anyone else not mentioned above!
Category Definition
I-COM defines this category as follows: Emerging technologies, innovative thinking for digital transformation, integrated data ecosystems, effective provisioning of business intelligence, improved means of collaborating, and end-to-end delivery of data-driven solutions that result in measurable, sustainable business value across an organisation and in the marketplace.
Category Objective
• Align the industry on the definition of MarTech Enablement. Showcase what is happening on the cutting edge of this space and the positive business impact it is delivering.
• Recognize the unique role that MarTech plays in empowering brands to grow by accelerating the utility of data intelligence within organisations – the dual benefits of Data Intelligence Creation by enabling the blending of data signals in novel ways, as well as Data Intelligence Activation across all brand-interaction touchpoints.
• Demonstrate MarTech’s contribution to business-transformative processes around advertising and marketing communications.
• Take a lead role in conversations that centre around Consumer Privacy, Data Stewardship, and Regulatory Compliance across markets.
• Provide case studies for companies to reference. Drive further application of MarTech to create meaningful change in the industry.
Judging & Criteria
50% of the scoring is based on the actual project results (for example: ROI, Attention, Response Rates, Purchase Incidence, Change in Repeat Purchase, etc.)
50% to the extent to which Data Creativity in Marketing Technology was applied in achieving those results.
Successful entries will address one or more of the following elements:
A. General Data Creativity Elements
• Creating New Insights from Multiple Data Sources
• Effective and Efficient Integration of Data
• Innovative Data Sourcing
• Analytics Creativity
• Using Insights to Evolve the Planning and Execution Process
• Employing Different Marketing Sciences
• Technology Innovation (in-house or with 3rd parties)
• Innovative Data Visualisation
B. Elements of Data Creativity Specific to the MarTech Category:
In a changing, addressable landscape where physical and digital have merged and brand interactions are actively managed by consumers, please demonstrate the value your submission has created through improvements in one or multiple areas:
• Agility – timely & efficient delivery of data intelligence that strengthens customer experiences
• Scalability – demonstrate the ability to extend/operationalize value originating from POCs/Pilots.
• Impact – articulate & quantify role in delivering against business strategies & goals.
• Innovation – new, and perhaps, unexpected ways in which technology has redefined how organisations operate.
• Analytics – real-time operationalization of ML/AI algorithms that created significant value.
• Modeling & Automation – democratisation of real-time data access for decision makers.
• Measurement Effectiveness – technological enablement of end-to-end impact measurement.
• Cross-functional Collaboration – effective partnerships that generate value.
• Data Stewardship – institutionalised processes for data privacy and compliance.
• Raising our collective Digital-IQ – thought-leadership and market-leading practices.
Who should enter?
• Advertising and Marketing Technology companies
• Pure-Play Systems Integrators
• Agencies and Consultancies
Marketers
• Data/Data Services Providers
Category Definition:
• Societal sustainability is the ability of a business to meet the needs of society without compromising the ability of future generations to create healthy and liveable communities. Socially sustainable communities are equitable, diverse, connected, democratic and provide a good quality of life. Driving societal sustainability could range from a balance of economic, social-including well-being, and environmental projects to create a sustainable way of life for the betterment of society.
• We define societal sustainability as an inclusive term to describe the creation of and maintenance of strong, cohesive communities to ensure that the members of the community have access to the resources and opportunities they need to lead fulfilling lives.
• Leveraging data, tools, and capabilities to partner internally or externally to drive long-term impact/change and address social sustainability issues such as human rights, health, safety, wellbeing, education and upskilling, reducing human impact on the environment, conservation as well as addressing issues of discrimination and social inequality.
• The ultimate goal: giving back to people and the planet, creating a sustainable future for all people, achieving meaningful change within society.
Category Objective
This award recognizes individuals, organisations, or communities that have made significant contributions towards creating a more sustainable future for all.
Award entries should showcase and encourage the application of data, analytics, insights, AI and more for the good of society and for the betterment of people’s lives today and in the future.
The category aims to Inspire companies and other organisations through case studies of successful examples that managed to achieve meaningful, long-term impact in our societies and communities.
Judging & Criteria
50% of the scoring is based on the actual project results (for example: ROI, Awareness, Degree of Process Improvement).
50% on the extent to which innovative and creative approaches were adopted in achieving those results.
Successful entries will include one or more of the following elements:
A. General Data Creativity Elements:
• Creating New Insights from Multiple Data Sources
• Effective and Efficient Integration of Data
• Innovative Data Sourcing
• Analytics Creativity
• Using Insights to Evolve the Planning and Execution Process
• Employing Different Marketing Sciences
• Technology Innovation (in-house or with 3rd parties)
• Innovative Data Visualisation.
B. Specific Data Creativity Elements to the Sustainability Category
• Demonstrate the degree the project has had a positive impact on society e.g. number of people reached, value to a community, and extent of the impact on societal sustainability.
• Outline the unique approaches to address societal sustainability challenges and the degree to which the project can be sustainable in the long-term e.g., upskilling communities, resources, promotion of equitable and inclusive development or change.
• Clearly articulate how the project can demonstrate measurable outcomes and put metrics on how to understand the longer-term impact on society e.g., project leading to long-term behavioural societal change.

Special Categories

Academic Collaboration

Social Good

To compete in the Special Categories of Social Good and Academic Collaboration, an entry must be competing in at least one regular Award Category. You should indicate in your Entry Form if you would like your entry to be considered for either of these Special Categories and pay the Additional Category fee accordingly.

Call for Entries

HOW TO ENTER