Launched by Snap Inc. in 2011, Snapchat is a mobile app that opens right to the camera — so you can send friends a quick photo or video of what’s going on, without having to type out a whole message.
Since its launch, Snapchat has experienced tremendous growth and innovation. With a large and engaged user base, Snap is an attractive platform for advertisers to connect with their customers through unique ad formats, such as Filters, Lenses, Snap Ads, and Story Ads.
But Snapchat’s unique platform, multiple advertising options and constant evolution have presented some challenges for advertisers. Marketers managing multi-channel campaigns need guidance to measure the impact of these activities accurately.
As an inaugural member of the Snap Marketing Mix Modeling Partner Program since August 2017, Nielsen has been at the forefront of incorporating marketing activity data from Snapchat into marketing mix models for advertisers.
> > Watch our on-demand webinar: Quantifying the Value of Snapchat Advertising: Best Practices for Marketing Measurement < <
Over the course of a year, Snap provided advertisers’ campaign data to Nielsen for use in over 80 marketing mix studies. Nielsen found that incorporating Snapchat into a marketing mix model is challenging for two reasons: it’s an evolving platform and advertising comes in a variety of media.
1. Snapchat is an evolving platform.
Snap is not only comparatively new, but it’s also constantly iterating, which can create additional challenges. New ad products and buy models have made huge strides in cost-efficiencies, but these drastic changes can also make it more difficult to incorporate Snap data into marketing mix models accurately.
2. Snapchat advertising comes in a variety of media.
Each type of ad has distinctly different user experiences and media delivery:
- Lenses: Historically 1-day executions, interactive Lenses deliver heavy impression levels in short bursts. Lenses evolved over time to alternative flighting patterns depending on objective.
- Filters: A form of camera marketing, Filters can run for comparatively longer periods (or bursts). Some location-based Filters can air at comparatively lower-levels.
- Snap Ads: Full-screen video campaigns during content consumption, Snap Ads generally air at robust impression levels with favorable continuity.
- Story Ads: Also appear during content consumption. Relatively new and based on tile impressions, Snap Ads can pose challenges when aggregating with other ad impressions.
These nuances, as well as varied levels of saturation and differing degrees of historical data granularity (by product), mean that measuring all as a single tactic (or with other digital activities) could produce misleading results.
Best Practices for Incorporating Snap In Marketing Mix Models
Snap advertising activities can and should be included in marketing mix modeling studies. Nielsen and Snap identified four best practices to ensure the most accurate and robust measurement.
1. Make sure your data comes directly from Snap.
Obtain activity data directly from Snap to ensure that you get the most robust data that includes all relevant activity at the market level. Data from other sources may include non-Snap activity or be at a level of granularity that does not allow the most accurate measurement, such as at the national level or not broken out by the type of ad.
2. Separate market and national-level data.
Keep lesser-quality national-level data for older executions separate from richer, market-level data to ensure accuracy.
3. Break out Snap as a separate variable.
To measure Snap properly, break it out as a separate variable in the model instead of bundling it with other non-Snap activity. If you don’t have sufficient Snap activity to get a measurable result as a separate variable, revisit Snap once enough activity has occurred to capture sufficiently robust historical data.
The level of impressions that are sufficient for Snap to be measured in a marketing mix model vary depending on the granularity of the data inputs. The more granular the data in the model, such as at the store or DMA level, the lower the impressions required for it to be properly measured in a marketing mix model.
4. Avoid aggregating data across ad types.
Snap ad formats vary by cost structure and execution patterns. Each type warrants a specific measurement approach. Brands leveraging multiple ad products may need to aggregate data independently if sufficiently robust activity is lacking.
When aggregating data, start with broad ad types (Snap Ads, Lenses, and/or Filters). If activity is still insufficient, prioritize max reach, burst-type products (e.g. most Lenses and select Snap Ads/Filters). Brands executing a less diverse product mix may prioritize key splits by buy type or detailed ad product. Be sure to make the products/buys clear when reporting results and note if any different flighting/cost dynamics have been captured jointly.
Measuring the Impact of Snap Advertising
Nielsen and Snap shared valuable tips for advertising on Snap in a webinar: Quantifying the Value of Snapchat Advertising, available on demand.
Josh Kowal, SVP, Marketing Analytics at Nielsen, and Garvin Roos, Manager, Quantitative Ad Measurement at Snap Inc., described the opportunities of the unique platform and best practices for measuring the marketing effectiveness of Snap.
They also presented findings from an analysis of Snap advertising performance in a major consumer product category, and shared how marketers can measure and understand the business impact of advertising on Snap.
Watch our webinar on-demand today: Quantifying the Value of Snapchat Advertising: Best Practices for Marketing Measurement.
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