connected past participle, past tense of con·nect (Verb)
- Bring together or into contact so that a real or notional link is established.
- Join together so as to provide access and communication.
There exists a fast-developing relationship between the connected consumer and the consumer-packaged goods (CPG) manufacturer. This relationship is enabled by mobile and fueled by social connections, in addition to new CPG channel routes to market, including online and direct-to-consumer (DTC). New market entrants are launching and growing their businesses by leveraging flexible delivery models and engaging directly with consumers via social media. This is especially true in the food and beverage industry sub-segments.
To counter this, major legacy brands are marketing their brand quality and investing in unique, differentiated brand experiences with the consumer. These multichannel brand experiences require data-driven analytics to enable channel and marketing decisions—and this can pose several challenges for CPGs. Here are some key issues I’ve observed:
Dynamic Investment Decisions
Data-driven analytics are needed to enable dynamic, flexible marketing investment decisions versus “stock” programs on a fixed calendar. Those are often inflexible or centered on rigid, as-is marketing processes over data-enabled insights.
Cross-channel Spend Expansion
Traditional advertising mediums are no longer the recipients of marketing spend. Social platforms, mobile message platforms, DTC third-party sellers, and the CPG manufacturers’ own DTC sites now all require marketing spend consideration. Traditional marketing mix models do not easily accommodate this new channel and consumer data.
As I highlighted in my Headless Commerce: What Is It and Why Does It Matter to CPGs? blog, DTC investments in CPG continue to rapidly progress and evolve. Consider these data points from the CGT/RIS Executive Council:
- 43% of consumers tried new brands in 2020, up from 32% in 2019.
- 70% of consumers switched brands during the COVID-19 pandemic because of supply shortages or because they couldn’t buy products directly.
- More than 57% of consumers aged 18-45 expect to continue shopping online at an increased rate.
- More than 50% of consumers say brands that regularly engage with them using immersive technologies would stay more top-of-mind.
Dealing with both structured and unstructured data is the “big data” challenge in the connected consumer space. This data flows into the marketing department and is often not integrated with sales, trade promotion, syndicated, and/or POS data. Agency-managed data is limited, siloed, and typically not all-inclusive of metrics that cross brands, channels, and consumer touchpoints. From an analytics perspective, more data and improved tools for analytics are highlighting the need for staffing additional business analysts—or even data scientists.
Our customers ask for our expert advice in this space, and AWS is uniquely positioned to help. We have developed an expertise in the data that CPG brands depend on with industry-leading services and partner solutions, like Amazon Redshift, Amazon Aurora, and Snowflake on AWS, to help them integrate data while enabling decisioning, advanced analytics, and automation. With these offerings, our customers can integrate shipment data, point-of-sale (POS) data, and consumer data from agencies and in-house data into one customer data platform. They can also link multiple back-office enterprise resource planning (ERP) and operational systems to make better sourcing, procurement, supply chain, and manufacturing decisions. In fact, we developed Amazon Redshift and Amazon Aurora to directly address our customer’s needs in migrating off inflexible, monolithic, locked-in database systems.
Let’s look at a few customer examples.
Zé Delivery, a subsidiary of Anheuser-Busch Inbev, faced a unique change as they rolled out consumer capabilities. With a rising number of people ordering beverage deliveries, Zé Delivery’s single database couldn’t scale adequately or manage enough servers to handle its rapidly growing user base. Zé Delivery used AWS Lambda and Amazon API Gateway to build a serverless infrastructure that iterates quickly and sustains growth. Now it can use powerful analytics to optimize its delivery system and improve user experience. As a result, Zé Delivery grew its user base by over 10x year over year, increased annual orders from 1.6 million to 27 million, grew its team from 60 to 300 employees, and optimized performance by region.
Dollar Shave Club wanted to find the best way to optimize storage and compute for its growing analytics environment. The company, which runs its ecommerce platform on AWS, wanted to try new AWS services to achieve this goal. Dollar Shave Club created a data lake using Amazon Simple Storage Service (Amazon S3) and Amazon Redshift, taking advantage of the Amazon Redshift Spectrum feature to query 60 TB of data. They now build analytical reports in five minutes instead of eight hours, saving hundreds of thousands a year by optimizing cluster sizes, and are putting those savings into research and development.