Clothing-Retail
Challenge
- Generate awareness of collections and sales through highly targeted online advertising
- Drive maximum ROI from online media spend
- Ensure full monetization, through remarketing, of visits (with no purchase) and cart abandonments.
VMM Approach
In line with VMM’s research-driven approach, we started with the implementation of an insights pixel on the web site. With the pixel in place, VMM started analyzing data about visitation and sales patterns and audience behaviors.
In addition, VMM analyzed third-party research sources for consumer insights including behaviors of site audiences and associated demographics, geography, and content category affinities.
Pacing and allocation were managed in highly dynamic manner based on the sales calendar plus analysis of ROI contribution by time of day and day of week.
Results
- VMM generated ROI of $25.69 for every $1 invested in media.
Hospitality
Challenge
- Efficiently drive room bookings (i.e. “heads-in-beds”).
- Deliver a $14 online cost-per-booking (CPB) utilizing results from peak season of the previous year as the basis for future performance.
VMM Approach
In the absence of client-owned historical audience data, VMM launched the campaign with an initial learning period in mind based on insights from key third-party research providers.
- VMM began collecting on-line booking data immediately to facilitate statistical analysis and audience insights.
- VMM incorporated remarketing from day 1 to ensure engagement with interested audiences.
Results
Through the utilization of statistically driven analysis, VMM’s optimization team identified and incorporated the key targeting variables — including location, day of week, and primary audience attributes — that were the primary drivers of performance.
- By the end of the 2-week learning period, VMM started delivering an average $4.66 CPB on a consistent basis.
- VMM delivered a 3x improvement in performance over the same period last year.
The VMM optimization team continues to analyze data on an on-going basis to drive progressive optimization, identify correlations, and improve overall forecasting of performance.
Transportation
Challenge
- Drive preference for the brand with affluent audiences especially downloads of informational brochures on the site.
- Demonstrate that ROI from online display media investments is comparable, if not better, than traditional print media.
VMM Approach
Based on insights from third-party research sources, VMM tested the following targeting tactics over an initial 2-week period:
- Ad placement within content categories that scored high, from an affinity perspective, with the target.
- Audience targeting utilizing third-party data segments reflecting demographic, geographic, social and lifestyle behaviors.
In addition, VMM adjusted daily spend levels on an on-going basis to determine the right balance between lead volume and an efficient cost-per-download (CPD).
Results
- Based on the statistical analysis of campaign data from the 2-week testing period, VMM identified the key variables that drove ROI and started applying those insights for audience buying.
- Through on-going monitoring and progressive optimization, performance stabilized at a $29 CPD.
- VMM drove the most optimal combination of volume and efficiency delivering higher lead volume than the industry trade magazines and a better CPD than the affluent consumer print titles.
Travel & Leisure – Case Study
Challenge
VMM was tasked by a travel ski destination with driving sales to skiers within a highly defined geography, while delivering a 5x return — $5 in bookings for every dollar of media spend. To support the campaign’s primary focus of delivering sales, a media budget for building brand awareness was created.
VMM Approach
Because of the limited geographic scope of the campaign and the highly targeted audience, the VMM team started out by developing custom data segments, combining 3rd party data from partners with in-market-for-skiing.
The VMM team employed a “full funnel” approach, consisting of prospecting, remarketing, and third party data buying to efficiently and cost-effectively drive prospects through the purchase cycle.
VMM managed bids and campaign pacing dynamically to adjust for environmental factors such as snow forecasts, and seasonal variables such as holiday periods. To maximize efficiency at the upper funnel, VMM applied contextual filters to the prospecting campaign, targeting weather, sports, and travel channels specifically.
Results
VMM exceeded the campaign’s goal by 210% by delivering over $10 in bookings for every dollar in media spend — outperforming all other media channels (direct and network buys) by more than 2x.
