Marketing campaigns generate large amounts of performance data from various online and offline sources. Analyzing this data is crucial to evaluate how well campaigns are achieving their objectives and determining areas for improvement. Here are some effective methods for analyzing campaign performance data:
Set Key Performance Indicators (KPIs) – The first step is to establish the key metrics that will be used to measure success. Common digital marketing KPIs include click-through rate, conversion rate, cost per acquisition, website traffic, leads generated, and sales. For traditional campaigns, KPIs may include brand awareness, purchase intent, and actual purchases. KPIs should be Specific, Measurable, Attainable, Relevant, and Timely to be most useful.
Collect Relevant Data – Data must be gathered from all channels and touchpoints involved in the campaign, including websites, emails, advertisements, call centers, point-of-sale, and more. Data collection tools may include Google Analytics, marketing automation platforms, CRM software, surveys, and third-party tracking. Consolidating data from different sources into a centralized database allows for unified analysis. Personally identifiable information should be anonymized to comply with privacy regulations.
Perform Segmentation Analysis – Segmenting the audience based on demographic and behavioral attributes helps determine which groups responded most favorably. For example, analyzing by gender, age, location, past purchases, website behavior patterns, can provide useful insights. Well-performing segments can be targeted more heavily in future campaigns. Under-performing segments may need altered messaging or need to be abandoned altogether.
Conduct Attribution Modeling – Attribution analysis is important to determine the impact and value of each promotional touchpoint rather than just the last click. Complex attribution models are needed to fairly distribute credit among online channels, emails, banner ads, social media, and external referrers that contributed to a conversion. Path analysis can reveal the most common customer journeys that lead to purchases.
Analyze Time-Based Data – Understanding when targets took desired actions within the campaign period can be illuminating. Day/week/month performance variations may emerge. For example, sales may spike right after an email is sent, then taper off with time. Such time-series analysis informs future scheduling and duration decisions.
Compare Metrics Over Campaigns – Year-over-year or campaign-to-campaign comparison of KPIs shows whether objectives are being met or improved upon. Downward trends require examination while upward trends validate the strategies employed. Benchmarks from industry averages also provide a reference point for assessing relative success.
A/B and Multivariate Testing – Testing variant campaign elements like subject lines, creative assets, offers, placements, and messaging allows identification of highest performing options. Statistical significance testing determines true winners versus random variance. Tests inform continuous campaign optimization.
Correlate with External Factors – Relating performance to concurrent real-world conditions provides additional context. For example, sales may rise with long holiday weekends but dip during busy times of year. Economic indicators and competitor analyses are other external influencers to consider.
Conduct Cost-Benefit Analysis – ROI, payback periods, and other financial metrics reveal whether marketing expenses are worth it. Calculating acquisition costs, lifetime customer values, and profits attributed to each campaign offers invaluable perspective for budgeting and resource allocation decisions. Those delivering strong returns should receive higher investments.
Produce Performance Reports – Actionable reporting distills insights for stakeholders. Visual dashboards, one-pagers, and presentation decks tell the story of what’s working and not working in a compelling manner that galvanizes further decisions and actions. Both quantitative and qualitative findings deserve attention.
Campaign analysis requires collecting vast amounts of structured and unstructured data then applying varied analytical techniques to truly understand customer journeys and optimize marketing performance. With rigorous assessment, strategies can be continuously enhanced to drive ever higher returns on investment.