Background
Across 2019–2022, I led the Advertiser Experience Design team when improving Performance Advertising offerings was the top priority within the revenue organization. Performance Advertising represents the lower portion of the advertiser's marketing funnel and, as a result, focuses on delivering lower funnel events like app installs, traffic to websites or applications, or delivering event conversions (purchases, sign-ups, etc.) on websites or applications.
During this effort's first couple of years, Twitter focused on increasing revenue from mobile application advertising. As a Design team, we successfully delivered this revenue growth through partnering to reduce the advertiser effort required to create and manage advertising campaigns and improve the product offering to become more performant in providing the desired results.
I helped the team accomplish this by establishing one of my direct reports as a Design leader on the cross-functional leadership team. This designer helped that cross-functional group identify and prioritize experience opportunities and helped the broader Advertiser Experience Design team understand the needs of customers coming to Twitter for lower-funnel outcomes. This way, we could efficiently leverage the breadth of resources and knowledge on the team to deliver the best results. This impact of the Design team was well-recognized across the organization, which increased our opportunities to scale this model of Design representation.
Toward the end of 2012, the prioritization within the performance advertising effort shifted toward improving performance outcomes for website advertising. However, we continued to operate with a Sr. Designer representing Design on the cross-functional leadership team for performance advertising.
During this time, it became apparent that Dynamic Product Ads was a significant opportunity for Twitter to grow this part of their revenue business. Dynamic Product Ads allow advertisers to serve ads to consumers that dynamically pull products from their online catalog based on the potential customer's past behavior or interests. Advertisers utilize Dynamic Product Ads to prospect (find new customers by showing them relevant products) or retarget (reach people who have already interacted with products on the advertiser's website).
Challenges
Twitter did not have an ad format specifically designed for commerce.
Dynamic Product Ads was a complex product offering that required the successful setup of event measurement, product catalogs, and ad campaigns.
The commerce team at Twitter primarily focused on organic engagement before the launch of Dynamic Product Ads.
Multiple cross-functional teams needed to align roadmaps to ensure the success of Dynamic Product Ads.
Approach
Dynamic Product Ads was a significant initiative for Twitter with an ambitious goal of releasing this new product offering in 2022. As a result, multiple efforts began at once. First, the Design team began exploring and testing consumer-facing ad format changes to support this new product offering. One successful exploration was modifying Twitter's multi-destination carousel that introduced a shopping-specific CTA and pricing information. Another outcome of that design process was a Collection Ad that enabled consumers to tap through presented products with an immersive experience through an increased visual footprint.
A multi-destination carousel that dynamically serves relevant products to the potential customer at the right time.
However, creating a successful experience for the advertising customer was this project's more challenging aspect:
Advertisers needed to implement website measurement using Twitter's pixel, a tag manager, or Twitter's Conversion API.
They needed to import the products and product information from their commerce site into Twitter.
They required a low-friction experience for creating, optimizing, and reporting on their campaigns.
To further complicate the effort, a different Design, Product, and Engineering team were leading Twitter's commerce efforts and were prioritizing organic acquisition over advertiser needs.
While the Product and Engineering teams were investigating the feasibility of delivering dynamic content within a Tweet that was historically immutable, I carved out time for a Sr. Designer to begin working on the project with the following goals:
Become an expert on industry practices by performing in-depth competitive analysis to understand how advertisers create and manage Dynamic Product Ad campaigns on competitor platforms.
Utilize existing customer research, competitive analysis, and knowledge of Twitter systems to map out the various product surfaces involved in the workflow.
Create an initial vision for the advertiser experience that focused on creating a seamless workflow that provided guidance and minimized errors.
An in-depth competitive analysis provided an extra data point for how the product might need to align with the broader industry.
Delivery
Through working out ahead, partnering with Product and Engineering, and collaborating across the Design team, the Sr. Designer delivered an initial end-to-end vision for the ideal customer journey. While it was apparent this wouldn't be the first iteration that shipped, the Design team anchored our partners on an ambitious vision that prioritized our advertising customers' needs. Additionally, this initial vision provided an opportunity to inform and build collaborative opportunities with the Commerce team as well as the various segments of the Ads Design to coordinate efforts.
The designer refined based on engineering investigations and near-term goals. The result was multiple prototypes that Research presented to customers for feedback. Design and Content Design incorporated that feedback into future revisions that received further assessment rounds with customers. The outcome was a clear direction for Twitter's Dynamic Product Ads product.
From there, Design worked with the cross-functional leads to define what would comprise the initial release. Some aspects of the workflow were reduced in scope, had constraints, or needed more exploration. We broke these down into smaller projects and utilized several designers on the team to collaborate cross-functionally and deliver the necessary changes across the breadth of Twitter's advertiser-facing surfaces.
Dynamic product ads are selected when setting up a new ad group to provide extra guidance and tailor the setup workflow to support the specific requirements of setting up this new type of campaign.
Results
Dynamic Product Ads launched in beta during Q3 2022, targeting a full launch in Q4 2022 ahead of the holiday shopping season. The new product demonstrated successful results.
Site Visit Campaigns
30-88% lower cost per click-through purchase
6-50% lower cost per site visit
Website Conversion Campaigns
24-74% lower cost per click-through purchase
Carousel with new CTA & Pricing Format
>70% improvement in purchase per impression
>40% decrease in cost per purchase
Collection Ad Beta Results
72% increase in average click-through rate compared to an Image Website Card
72% increase in dwell longs
69% increase in average conversions per impression
Takeaways
Although the team and I did not get the opportunity to deliver our full vision for Dynamic Product Ads, I learned some lessons and reinforced some beliefs throughout the process.
Planning ahead to give the designer time to analyze gathered research and competitive insights established Design as a subject matter expert on the cross-functional team.
Dedicating a "lead" for a large project while also helping to facilitate collaboration and support allowed the project to move forward at pace.
Designing and validating ideal workflows early in the product development process helped inform the product requirements for the first milestone and anchored difficult decisions in how the team took the first step to get to the future state.
Encouraging Design collaboration throughout the process enabled the broader team to break down and support multiple efforts in parallel and also provided shared knowledge to allow the team to continue executing through attrition.
