Our client, a large global Media & Entertainment provider, had been the preeminent player in its category for years. Users and revenues went up consistently quarter after quarter. However, a new competitor app with a slightly different value proposition was taking significant market share and was emerging as a real threat. The Marketing department was tasked with stopping the user leakage by running several expensive and eye-catching campaigns. These campaigns were creatively ambitious and targeted a wide variety of segments and products. However, it was not clear how effective each of the campaigns was until long after the campaign had ended. There was a continual expansion of KPIs, and each campaign usually had a positive impact on one or two KPIs, making it difficult to evaluate whether a campaign was successful or not. There was almost no mid-campaign adjustment, even though the client had significant user data, and the campaigns ran several weeks. Because of the ambiguity, each campaign ran longer and longer (and cost more) before a decision could be made about its effectiveness. Further, initial analysis showed that a significant percentage of the campaigns had limited or zero impact on the most important KPIs.

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If the client could better align its campaigns to reach its KPI targets, it could adjust failing campaigns, turn up the volume on successful campaigns, and derive much higher Marketing ROI at a critical competitive time.

Although the client had access to terabytes of user data, there was a cultural norm of KPIs being added regularly and priorities reshuffled. Further, they had a significant Insights and Analytics Department, but several positions were unfilled and as the economy turned would not be filled for the foreseeable future. Any demand for new data collection or analysis would take months to be delivered.

The team reviewed existing data collection, reporting practices and follow-up actions as well as performance of individual campaigns and made the following recommendations.

• KPI Prioritization– The Artemis Team reviewed the dozens of Marketing KPIs and re-set clear priorities.
• Campaign Performance Analysis. The team tracked the performance of each campaign over the past 4 years and assessed whether or not the campaign had an impact on a meaningful KPI.
• There were several expensive campaigns that had no discernable impact on major KPIs.
• Translating Behavior to Preference. The client had two principal families of KPIs.
• Behavioral - KPIs are easy to track – did the user click on a button or not? Results are available in real time so actions can be taken. Preference KPIs are more difficult, as they involve a change in a user’s perception of the brand. These scores were only reported 6-8 weeks after completion of the campaign. The team looked at how actions (behavior) had shaped preference in previous years and identified Behavioral KPIs that correlated positively with Preference, allowing a temporary measure of success. The team also recommended a change in data collection practices so panels were polled more quickly and frequently, so organic preference data was available long before the campaign had ended. This allows the client to make changes in the scheduling, placement, and frequency of campaigns depending on performance.
• Dashboarding– The Marketing team was looking at large collections of data in spreadsheets.
• The team developed a dashboard which would allow the team to focus on a precious few KPIs–the baseline, the current value, and the expected value by the end of the quarter. This allowed fact-based conversations to happen faster and actions to be taken more decisively.