The data exists—and marketers have an array of methods to choose from when assessing digital ROI. Marketing mix modeling, for example, is a tried and tested approach to assess the impact of marketing on business results. While it has worked well in paid media (e.g., print campaigns, TV spots, and display advertising), marketers have had difficulty applying it to social media, primarily because “earned media” channels like social networks are a two-way street. Companies send out their messages, but consumers can also voice their opinions about these companies, comment on their products, and discuss their services.
Social media has four primary functions—to monitor, respond to, amplify, and lead consumer behavior—which can be linked to the “decision journey” people take when buying a product or service. Being able to identify exactly how, when, and where social media influences consumers at each stage can enable executives to craft marketing strategies that tap into social media’s unique ability to engage with customers. In their traditional forms, ROI analytics are not up to this level of complexity, but in combination with next-generation tools, they can deliver results.
The fundamentals of ROI marketing analytics remain solid; but to extend them to digital marketing, McKinsey has developed three innovative analytical methods to help marketers better understand the impact that targeted marketing responses have at individual touch points along the consumer decision journey. When employed in combination, they can provide useful new insights into what works in digital marketing, while offering a solid starting point to optimize social media marketing.
No method exists to reduce the multitude of social media KPIs to a common denominator for comparison across different social media platforms like Facebook, Twitter, or blogs. For traditional media, gross rating points (GRPs) fulfill this function by measuring the advertising intensity of a campaign as a whole. McKinsey has created an online analog. Social media GRPs is a metric based on the number and reach of company-related postings across social media. It serves as marketing mix model input to determine the impact of social media on business performance. Various sources provide the information needed: from monitoring of social media panel data to platform-specific tools such as Facebook Insights. Compared with classic GRP data, social media GRPs have a critical added dimension: sentiment. After all, social media postings can also be negative, making it necessary to differentiate between negative, neutral, and positive social media GRPs.
By using social media GRPs, marketers can integrate social media into their marketing mix models to determine its effect on sales and profits. Marketing mix models also enable teams to develop response curves—akin to the ones used for traditional media—to optimize their marketing mix based on expected returns.
Which factors determine company performance in social media? Marketers can answer this question by using an approach that systematically analyzes buzz and identifies its key underlying drivers. The buzz monitoring approach addresses central consumer interaction questions and—since it is central to the “monitor” stage—is the premise for responding to, amplifying, and leading consumer behavior. When in the buying process do users voice their opinions—before acquiring the product or afterwards? What are the dominant themes—the product, service, or the price? And where does the discussion take place—in forums, on Facebook, or in blogs? Buzz monitoring answers these crucial questions.
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This piece originally appeared on the McKinsey & Company Telecom, Media and High Tech Extranet
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