Data analysis helps marketers identify trends, interpret consumer behavior, and craft effective customer experiences for measurable success. Analytics can provide an objective, results-oriented platform for discussion where marketing agencies and companies find the most impactful and cost-effective campaigns together.
While creative talent and stunning visuals can trigger powerful emotions, quantifying the monetary value of marketing and advertising can be challenging. Analytics provide a systematic study of “what works” using the scientific method, and it helps draw a clear line from campaigns to company profits. We’ll take a deeper look into the power of analytics and a case study by Mabbly that examines the science of “What Makes Employees Happy.”
The most important aspect of data analysis is collection, and marketers have been collecting customer information for hundreds of years. Direct mail campaigns could measure response rate by counting replies, perform A/B testing by sending different messages to an experimental group, and allow for segmentation of an audience by different demographic groups. Who wouldn’t want a discount, coupon, or promotion for exactly what they need, at their local store, during the season they need to buy it?
Modern analytics builds upon the mailed envelopes and postcards in the past, but data collection and modeling are amplified by automation, cloud storage, and location independent collaboration tools. Electronic media can track small interactions, such as opening an email, or looking at a specific post for a certain length of time. As marketing continues to evolve, companies with advertising platforms such as Google and Facebook add more powerful features for analysis and projection.
Case In Point: Mabbly Cultural Case Study
Mabbly, a digital marketing agency recently completed a case study on “What Makes Employees Happy.” We categorized 937 employee reviews for the Boston Consulting Group on Glassdoor.com to find the factors most correlated with morale in the workplace. Metrics such as recommendation rate and star rating (1-5) were used to group reviews into positive (4-5) and negative (1-2) groups for further correlation.
Phrases and themes in the written feedback section of each review were tallied and grouped into multiple sectors: employee development and care, atmosphere and environment, work, and management. The most satisfied employees were likely to reference excellent people, interesting and meaningful work, open opportunities, and generous compensation with benefits.
The data was compiled individually and presented graphically to help visually identify trends that show which factors are most frequently referenced, and how strongly the employee communicated their feelings. Negative reviews often mentioned politics, dysfunction, and unfair work distribution as unenjoyable, but still frequently included positive remarks about compensation, benefits, and excellent people.
The results from the BCG study provide insight to how company culture and leadership can drastically affect employee retention and satisfaction, and the analytic visual tools and presentation are powerful maps for future decision making.
Analytic marketing tools are still in their infancy, and early adoption can give agencies a competitive advantage with proven, measurable results. Ongoing research allows marketers to hone their craft with precision as both art and science. Regular upkeep with analytics can help identify trends in real-time, and provide feedback to find which campaigns are most effective for each market.
As statisticians, economists, and developers collaborate, these tools will provide marketers with powerful forecasting tools, automatic collection of rich data sets for deep segmentation, and mathematical modeling for studying statistical correlation between marketing campaigns and consumer behavior.