"With Evolving Consumers' Preferences, Cloud & AI Will Play A Central Role In Shaping The Adtech Industry In 2022" Geoff Soon, Managing Director, Snowflake

In conversation with Marketing In Asia, Mr Geoff Soon Managing Director South Asia, Snowflake, shares his insights on what adtech can mean to the Media and Entertainment Industry in 2022, Role of adtech in content personalisation and content contextualisation, leveraging AI/ML in media workflow solutions & much more. Read the full interview

"With Evolving Consumers' Preferences, Cloud & AI Will Play A Central Role In Shaping The Adtech Industry In 2022" Geoff Soon, Managing Director, Snowflake

Shed some light on what adtech can mean to the Media and Entertainment Industry in 2022

 

Adtech or Advertising Technology is going through profound shifts as digital media consumption accelerates. With evolving viewers' and consumers' preferences, Cloud and Artificial Intelligence (AI) will play a central role in shaping the adtech industry in 2022 and in the years to come. With real time access to reliable and clean data, companies can analyse and enrich customer data to increase campaign effectiveness, drive media optimisation and define media mix, enhance content development, acquisition and monetisation, and improve content personalisation and optimise recommendation engines.

Adtech solutions such as Demand-Side Platforms and Data Management Platforms (DMPs) utilise automation, enabling media organisations to analyse business data significantly faster and gain access to business insights. With the capability to generate real time insights, media organisations can optimise investments and direct ad spend towards campaigns and initiatives for improved business results.

In addition, by using artificial intelligence (AI) and machine learning (ML), companies can predict viewing patterns and preferences to offer relevant content based on users' activities and choices. Using algorithms, content platforms collect and analyse data to provide consumers with personalised content to keep them constantly engaged. Data analytics augmented with AI enable businesses to get unique insights across multiple channels in real time and deliver excellent user experiences.

Lastly, as data privacy gains more attention, gaining insights into audience preferences while complying with consumer privacy regulations is just one of the hurdles companies must overcome to provide secure, engaging and personalised user experiences. By leveraging secure data sharing technologies, media and entertainment organisations can collaborate and create linkages with partners, customers, and technology providers, that enable person-level marketing without compromising privacy.

 

The media and entertainment (M&E) industry continues to undergo a transformative process, and adapting to changes in consumer behaviour and preferences, is imperative. Please share with us how Adtech can help the M&E industry in content personalisation and content contextualisation.

 

 

The demand for hyper-personalised content and immersive entertainment is growing, and leveraging technologies to extract valuable insights is crucial to decision-making on content development.

With data on consumers' consumption patterns and habits, companies can enhance content development and acquisition and make better decisions on which projects to fund or which channels to launch their content.  Media organisations can also tap on the capabilities to share and match first-party data in a secure, privacy-compliant manner, generate richer audience insights, and run targeted campaigns that drive real, demonstrable business value.  With this data sharing environment, organisations can share and access first-party data to augment internal data and gain better insights without exposing personally identifiable information (PII).

By tapping on data from publishers and technology companies, organisations can analyse every click, hover, or stream across devices to create a comprehensive view of subscribers, understand drivers of subscriber acquisition and retention, and increase average revenue per user (ARPU) without data ever leaving their environment.

 

Cloud data sharing empowers media and entertainment organisations to optimise their most valuable data assets in achieving their business objectives. For business efficiency, sharing live data with internal and external business partners to optimise spend, provide superior customer service, and streamline operations. Moreover, as cloud data sharing eliminates information silos and enables seamless and secure data sharing, companies within the media and entertainment sector are able to create 360° views and deliver greater content personalisation and contextualisation.

 

How can adtech leverage AI/ML to underpin media workflow solutions?

 

Machine learning platforms provide users with the tools necessary to develop, deploy, and improve machine learning — specifically, machine learning algorithms. Machine learning platforms automate data workflows, accelerate data processing, and optimise related functionality.

 

As the amount of business data increases, so does the importance of applying machine learning and AI strategies to turn data into insights, drive business decisions, and improve products and services. Machine learning platforms and tools combine intelligent algorithms with data, enabling organisations to derive business insights and deploy new solutions at scale.

 

Some of the benefits that ML/AI technologies offer businesses include:

  • Data-driven business decisions
  • Improved products and services
  • Time and energy saved through automation
  • Shared insights, as users can share data, models, and related information with collaborative tools
  • Simplified, scalable data science via user-friendly features and out-of-the-box solutions
  • Optimised experimentation through data visualisation, augmentation, and preparation tools

 

With access to massive amounts of data and artificial intelligence technologies, businesses can improve engagement with their customers, automate business processes, and improve productivity and revenue.

Leveraging AI and predictive analytics, businesses can identify the reasons for customer churn, identify risk by behaviour or interaction changes, which helps companies create proactive retention strategies. With offers being customised for each customer by looking back at their history and personal profile, hyper-personalisation becomes more effective for marketing. Combined with insights on market trends, insights derived from company data with the help of AI, can help companies improve their products, services and offerings.

 

How can Advertising, media and entertainment companies leverage THIRD-PARTY DATA to enhance analytics and how does Snowflake enrich data and unlock new insights faster?

 

Advertisers, media, and entertainment companies can leverage third-party data to gain a robust understanding of their customers, gain granular insights about their audience, optimise personalisation and reach and improve investment returns. However, with challenges in sourcing, maintaining and using third-party data, marketers have limited ability to realise its full potential. With the emergence of new technologies and platforms, challenges in using third-party data such as sourcing and maintaining data quality as well as ensuring compliance with data privacy laws and regulations, are now being addressed.

 

Data collected by the company directly from its customers is called first-party data. This type of data includes CRM data, email databases, subscription data, website behavioural data, and analogue data such as event attendance or surveys completed at a retail location. While first-party data provides valuable insights into understanding customers, shifting from basic analytics to advanced marketing analytics can be achieved by tapping third-party data. Third-party data is obtained from sources that did not collect it directly from consumers. Third-parties such as data brokers, identity solutions providers and data exchanges, collect large amounts of data from other platforms, apps and websites, and then package data sets for use by others.

 

Third-party data is one of the most cost-effective ways to enhance a company's first-party data, and it enables finer segmentation and personalisation as well as greater scale and audience reach.

 

Third-party information comes in support when the experience of the user needs to be optimised. For example, to retain a player base and increase engagement, gaming companies can achieve these goals by improving player experience. In free-to-play mobile games that create revenue with advertisements, player experience can be an issue, where the risk of players leaving is rampant when the game has a lack of new content offerings. LiveOps or live operations are used by game publishers to optimise the experience of a player in real-time.

 

To understand customer behaviour and preferences, advertising, media, and entertainment companies must unlock data-driven insights. Organisations need to scale their use of data and benefit from advanced analytics while complying with consumer privacy regulations and reducing costs. Through data-driven decision-making, advertising, media, and entertainment companies can deliver personalised content and experiences, retain customers, grow their business, and build a data-driven future.