AWS for Industries

Fast track data-driven insights for advertising and marketing with Databricks accelerators on AWS

Optimizing spending in the advertising and marketing industry—whether that means delivering more personalized campaigns to customers or attracting higher-quality users—is always an iterative process. Data scientists and data engineers are constantly maneuvering through advertising, marketing, and sales data to measure effectiveness and uncover insights that improve the way their companies connect with consumers. To help speed this process, Databricks created several solution accelerators designed specifically for the advertising and marketing industry.

The data dilemma

Advertisers and marketers are in a conundrum: they don’t have all the data that they need in one place, and can’t get the value they need from it. Advertising and marketing firms are focused on audiences and outcomes, not building and managing complex data architectures. Constructing a data platform and running analytics is complex, expensive, and time consuming and requires significant resources to maintain. Because of restrictions and silos, copying and freely pulling data is an arduous task. And different departments need different things from data, making collaboration difficult in the absence of seamless access and usability.

Databricks understands these challenges well, which is why it built a data lakehouse platform for data, analytics and AI that accelerates innovation, facilitates collaboration, and improves productivity. Using Databricks, organizations can transform and access their historical and real-time data, both structured and unstructured, without having to build and manage the infrastructure to do it. Because all the data is managed from a simple data lake sitting on top of Amazon Simple Storage Service (Amazon S3), organizations can now cost-effectively pursue analytics, ML and artificial intelligence (AI) initiatives.

Although Databricks provides a horizontal data lakehouse platform, it is constantly thinking of how to deliver new technology to solve problems that are specific to verticals. For example, advertisers and marketers need to use data to understand their audiences better and allocate budgets more efficiently. In response, Databricks has launched its Advertising Intelligence solution, which consists of three specific solution accelerators.

The Customer Segmentation solution accelerator, the Multi-touch Attribution solution accelerator, and the Sales Forecasting and Ad Attribution solution accelerator make it easier for customers to advance their pipelines and answer questions that they could not answer before. These accelerators speed time to value and cater to the contextual analysis, measurement attribution, and verification that are critical to marketers and advertisers.

By using Databricks solution accelerators to bridge the gap between business goals and technology, advertisers and marketers see significant benefits:

  • Faster time to value, faster time to market
    • A simple setup means that businesses can start running notebooks immediately to collect feedback. With faster campaign refinement, businesses can more quickly realize new revenue streams.
  • Reduced costs
    • Because there is no data lake house to maintain and customers pay for only what they use with billing from Amazon Web Services (AWS), advertisers and marketers save money.
  • Simplified collaboration
    • Databricks’ pre built models and native integration with AWS provide users with a single view of their data, supporting cross-organization productivity for all data, analytics, and AI use cases.
  • Agility
    • Databricks designed the accelerators to be customizable models, boosted by native integrations with AWS. Users can incorporate nearly any type of data—streaming, raw, or curated—and view results through the business intelligence tool of their choice. As a result, businesses can rapidly respond to fluctuating needs and circumstances.
  • Time savings
    • Employing ML-driven models saves data engineers and data scientists months of development time, empowering them to do more in less time.
  • Privacy and security
    • Both Databricks and AWS offer services to further secure data. Databricks on AWS uses secure single sign-on (SSO) for ease of access and offers first-party data consolidation.
  • Efficiency

Databricks Solution Accelerators: Speedways to innovation

Databricks’ Advertising Intelligence solution accelerators simplify the path to understanding how advertising and marketing campaigns influence sales using prebuilt models that customers can apply across their lakehouse. By migrating data and AI workloads to Databricks on AWS, businesses can incorporate the accelerators and get started immediately. Packaged in a series of notebooks, the accelerators are quick to set up and provide immediate feedback, letting advertising and marketing teams accomplish in weeks what would otherwise take months. Supported by the compute power and nearly unlimited storage of AWS, customers enjoy more flexibility, scalability, and reliability at a lower cost than in-house builds.

To support users from different lines of business, these accelerators were made to meet the different goals of multiple teams—sales might be more interested in forecasting; marketing, in identifying new target markets or promotions; product teams, in the iterations that their customers want them to prioritize.

Although all these accelerators work together, businesses can apply them as stand-alone projects or they can be layered, beginning with Customer Segmentation, moving into Multi-touch Attribution, and then on to Sales Forecasting and Ad Attribution. Ideal for testing, the Customer Segmentation accelerator can be applied as a first layer for a foundation or as a final layer to accelerate a business’s understanding of its audience at either end of the campaign. Because Databricks helps teams to gather insights from structured and unstructured data, these accelerators can be used for multiple campaigns.

Bring foresight to future campaigns with the Databricks Sales Forecasting and Ad Attribution accelerator

Gathering data-based insights on how past campaigns have fared is valuable, but having a strong grasp on how future campaigns are likely to perform is even more valuable. With the Sales Forecasting and Ad Attribution accelerator, businesses can tap into historical data analyses to inform a future scenario and explain fluctuations in key performance indicators. Ideal for agency analytics or media planning teams, this accelerator predicts tomorrow’s conversions based on yesterday’s budget allocation, making optimizing even the most complex media mixes easier.

The Sales Forecasting and Ad Attribution accelerator uses ML models to help teams better understand what data will resonate with which customer segments. By pulling and preparing sales, ad engagement, and geographical data from a variety of historical and current sources, teams can identify the impact of influencing factors—such as seasonality, competitor actions, and promotions—all on a unified platform.

Refine personalization with the Databricks Customer Segmentation accelerator

No household is the same—one person in a household might be the primary grocery shopper, for example, and the other manages finances and wants to know about great banking offers. Or maybe certain customers in a target demographic tend to use coupons and others don’t. How can marketers and advertisers determine who will be responsive to a particular campaign, and then turn that into a unique data cluster? The Customer Segmentation accelerator helps retail and ecommerce marketers and advertisers to implement granular personalization without groups at scale. More of an offline accelerator, this model can be used for A/B testing before or after running a campaign so that teams can make more informed changes.

Using the Customer Segmentation accelerator, Databricks takes first-party customer data and interaction data—for example, from an advertiser or a business website—and uses a machine learning algorithm to generate insights. Clustering to form various segments more efficiently provides marketers and advertisers with information on how to target more granular groups with different content, yielding higher engagement and conversion rates.

Benefits include

  • easier identification of target customer groups;
  • highly granular customer segmentation that generates more reliable behavior-based purchasing predictions;
  • improved conversion rates that result in more relevant campaigns; and
  • collaboration-friendly data segmentation that democratizes use across teams and improves the products and services that a business offers.

To learn more, read the Customer Segmentation solution accelerator explainer.

Understand impact with the Databricks Multi-touch Attribution Accelerator

For marketers and advertisers, there’s no challenge in collecting data around sales numbers—the challenge is in determining which marketing and ad campaigns on which channels drove those sales. The Multi-touch Attribution accelerator helps companies connect those dots by issuing conversion credits that explain the different levels of influence that parts of a campaign had on target audiences. For example, marketers might discover that running LinkedIn ads targeting mid funnel customers was far more impactful than the email campaign that targeted top-of-funnel buyers. With these new insights, businesses can consistently optimize their ad spending to produce higher returns. The Multi-touch Attribution accelerator comes with prebuilt code, sample data, and step-by-step instructions that Databricks customers can immediately input into their notebooks.

This accelerator lets customers employ a variety of heuristic-based attribution methods and data-driven methods, including a time-decay model and Markov chains. Customers who use the Multi-touch Attribution solution and Databricks see a 45–60 percent increase in campaign revenue, a 22 percent reduction in the operational costs of running their data pipelines year over year, and a 30 percent improvement in productivity across data teams.

Benefits include

  • single-view collaboration through a near-real-time dashboard that teams can use to determine how to spend more effectively across channels;
  • insight into behaviors across the customer journey with customizable conversion credits from the first and last touch;
  • the ability to integrate new marketing channels with models that evolve with customer campaigns;
  • increased ability to optimize future campaigns based on conversion-credit results with media-mix optimization; and
  • methods for taking more data-driven investment strategy, resulting in more sales.

To learn more, read the Databricks Multi-touch Attribution solution accelerator explainer.

The Sales Forecasting and Ad Attribution solution accelerator lets businesses

  • get a better idea of how their investment will perform with granular forecasting, improving marketing return on investment;
  • more easily focus on best-performing channels with quick insights on a near-real-time dashboard that maps or forecasts ad-impressions-to-sales;
  • gain agility by easily integrating new data sources whenever they need to;
  • provide a better experience to customers with more personalized content; and
  • reduce costs associated with the manual tasks typically used to gather these insights.

Read the Databricks Sales Forecasting and Ad Attribution solution accelerator explainer to learn more, or watch the video.

Enhance business data pipelines with Databricks accelerators on AWS

Born on AWS, Databricks uses Amazon S3, object storage built to retrieve any amount of data from anywhere, for SQL analytics and offers more than 20 integrations so that businesses can do more with their data.

Check out the Databricks page on the AWS Marketplace to get started with Databricks on AWS, and visit the AWS industry page for ready-to-deploy advertising and marketing solutions.

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Debu Sinha

Debu Sinha

Debu is a Senior Specialist Solutions Architect at Databricks focused on implementing/optimizing machine learning and deep learning capable pipelines at scale. Previously he has co-founded a real-time identity graph management and analytics company called Throtle onboarding. Before that, he founded a nonprofit org in India that aimed at increasing education access to remote parts of India using virtual classrooms. In his current role, he interacts and aligns strategically with the technical and business leadership of Databricks Enterprise customers. He is leveraging his strong technical background, love for public speaking, and effective communication with customers to understand their business and technical strategy and challenges. He regularly engages in architectural design and whiteboarding sessions with customers as they see him as a trusted advisor. As a Senior Solutions Architect at Lifion by ADP, Senior Engineer at V12 group, and Bank of America, he has spearheaded multiple projects involving streaming and machine learning capable pipeline creation and optimization. his passion for cloud computing, machine learning, and distributed systems began while working on his Master’s research thesis on Machine Translation at Johns Hopkins University.

Layla Yang

Layla Yang

My name is Layla Yang. I am a Solutions Architect at Databricks. Before Databricks I started my career in AdTech industry focusing on building Machine Learning models and data products. I spent few years at adtech startups to design, build and deploy automated predictive algorithm into production for real-time bidding (RTB) plugged in major Ad Exchange and SSPs. My work also included MMM (media mix modeling), DMP user segmentation and customer recommendation engine. Currently I work with start-ups in the NYC and Boston area to scale their existing data engineering and data science efforts leveraging Apache Spark technology. I studied physics back in university and I love skiing.

Hari Radhakrishnan

Hari Radhakrishnan

Hari Radhakrishnan is a Senior Partner Solutions Architect in advertising and marketing technology at Amazon Web Services (AWS). Leveraging his industry experience, he is responsible for solution architecture and technical strategy for advertising and or marketing technology partners on AWS. He recruits and helps partners develop solutions on AWS. Outside of work, he enjoys spending time volunteering and backpacking.

Venkat Viswanathan

Venkat Viswanathan

Venkatavaradhan (Venkat) Viswanathan is a Senior Solutions Architect at Amazon Web Services. Venkat is a Technology Strategy Leader in Data, AI, ML, and Advanced Analytics. Venkat is a Global SME for Databricks and helps AWS customers design, build, secure, and optimize Databricks workloads on AWS.