Social media data powers today’s data-driven CMO. 

Social media data informs many marketing-related activities, from ensuring that a company’s target audience knows about key products to updating executives about campaign strategy and performance. 

But social media data is just part of the equation. CMOs must process, analyze and assess data from numerous channels – social, mobile and more – to extract useful insights that will translate to improving bottom line business revenue. 

A CMO’s decisions and marketing programs must now be informed by data rather than intuition, past experience, hunches and assumptions. 

The Expanding Data Universe 

The continued expansion of enterprise data is predicted to contain nearly as many digital bits as there are stars in the universe by 2020. Data-driven organizations prioritize collecting the right data — and by right data we mean every piece should address a fundamental business question. 

How does social fit into this data-driven organization? The socially-enabled business adds to the 360-degree view of customers and key audiences by integrating unstructured content that captures consumers’ interests and needs.

Marketers are now allocating more of their budgets to social, mobile and marketing analytics. In five years’ time, social media spending is predicted to account for 24 percent of total marketing budgets, and marketing analytics is expected to grow to 11 percent of the total marketing budget in the next three years. 

Why are analytics tools and services becoming increasingly important? For any data – regardless of its source – to become meaningful and actionable, it has to be analyzed.

In a multichannel, multi-screen and multi-device world, marketers can’t drive loyalty, deliver a seamless consumer experience or engage key audiences based on assumptions. However, marketers still face challenges using these capabilities and proving ROI from investments.

According to Duke University’s recent survey of 288 CMOs, just 13 percent of marketers say they can effectively measure social data accurately. Turn that on its head and it means almost 90 percent can’t demonstrate the impact of social media spend on company performance.

A Forbes Insights report (registration required) also revealed that 33 percent of executives are “grappling with a mix of technologies that support data gathering, analytics, insights, programmatic advertising and planning – with little coordination.”

The Never-Ending Quest for ROI

Proving ROI is a never-ending challenge for marketers. Data must directly translate to leads generated, conversions and other business metrics to prove its worth. 

How can marketers prove ROI with social media data/analytics? They must dig deeper. Accurately measuring the billions of social data items and then turning that data overload into useful insights is undeniably tough.

Most social networks provide advertisers with a number of click throughs, views or stats. However, how do marketers determine what someone does once they click on Facebook and arrive on a landing page? How many of those views translate to a site visit, and of those site visits, how many culminate in a purchase?

Marketers must track via code to determine if a customer took a specific action. Did the landing page visit result in a sale? Did the potential customer drop off somewhere within the marketing funnel, and if so, where? Is the wrong content reaching the wrong people, resulting in failed leads? Are the wrong people coming through the marketing funnel?

Marketing Funnel Under the Microscope

Historically, the marketing funnel represented the customer journey from initial product awareness through point of purchase:  Awareness, interest, desire and action (AIDA).

It’s an approach that’s worked for generations. But not anymore. 

Consumer behavior has changed beyond recognition in the past five years. Those traditional ways of thinking about the consumer (such as the marketing funnel) don’t apply any longer. AIDA still has relevance, but the consumer decision journey is now subject to many different moments of influence, making it harder than ever to analyze. There’s far more data and fragmentation - Web, social and mobile – than ever before.

Programmatic ads, or using automation and real-time bidding in placing ads online, in social media and via mobile and video, is one way marketers have been reaching the right potential customers. In fact, 67 percent of those surveyed in the Forbes Insights report indicated that programmatic “has helped improve segmentation and targeting of customers.”

Basically, the targeted automation helps connect the right ad with the right customer at the right time – a key step in getting that customer into the marketing funnel and toward a purchase.

However, big insights and data science are now stepping into the limelight.

Audience Insights, Intelligence and Data Science

Traditionally, extracting industry or customer insights from social data has been limited to analyzing brand health and measuring sentiment (positive, negative or neutral). 

Machine learning technologies now enable companies to gain more nuanced insights into market interest and can surface customer intent to churn, purchase and more. This is a new era in social data analysis, where you can move beyond the basics of sentiment analysis to answer questions such as: Which products are people considering buying? How satisfied are my customers? Are they thinking of leaving me? Which parts of my service prompt the best reviews?

In addition, a combination of big and small insights is giving marketers a far greater understanding of potential customers. At an audience level, anonymized and aggregated social data can provide CMOs with insights that enable them to improve marketing efficiency, spot new trends, identify new audiences and more.

On the flipside, social logins have become standard and provide businesses with small insights into consumer interests, preferences and potential product needs. Everyone from Airbnb to American Express allow users to quickly register and log in with existing social identities, such as Facebook and Google. 

The small insights that can be derived from this data enable better personalization, product recommendation and a better user experience. Social intelligence enables CMOs to question assumptions, formulate hypotheses and fine-tune the calculations. Ultimately, helping to improve and prove social ROI.

Data-driven CMOs are primed to reap the rewards. However, these CMOs must be strategic about tying data insights back to the customer journey and driving more customers on their path to purchase. This is where the data “rubber” meets the “customer and purchase” road, and is imperative to overall company innovation, profitability and success.

Title image by Hani Jajeh