“Data should be the oxygen of any marketing and advertising organization,” Michael Kaushansky notes in a recent post about big data analytics on Online Metrics Insider.
With a growing arsenal of customer data available from multiple channels, including the web, mobile, social, chat, email, and voice, as well as powerful analytics and customer strategy tools to draw from, chief marketing officers (CMO) are well positioned to take advantage of big data and big data analytics to do their jobs more effectively, he says.
Just 37% of company projects make use of, or even request, available market analytics for decision making, according to this blog post from The CMO Survey. Delving a bit further into the use of marketing analytics, The CMO Survey finds that less than half of organizations that evaluate marketing analytics actually use these tools.
Without question, there are myriad opportunities for CMOs to use big data to help fulfill their marketing strategies. These include:
1. Unearthing customer sentiment about product or services issues. Customers share a great deal about their likes and dislikes when it comes to products as well as the ease or challenges of doing business with companies. CMOs can act on these insights quickly to defuse the potential for customer dissatisfaction or churn.
2. Identifying and acting on the types of products that customers truly want based on structured and unstructured customer feedback. Companies have a variety of ways to gather customer feedback, including customer surveys as well as customer sentiment that’s shared through social media channels. In addition, analytics can be used to decipher customer sentiment that’s shared in recorded contact center interactions with agents.
3. Gaining a deeper, more visual understanding of the multichannel customer journey and then acting on these insights to improve the customer experience. Customers use multiple channels as they conduct research about products (company web sites, online forums, social media channels) and complete transactions (online, mobile, in-store). CMOs can aggregate this data from across different channels and then use analytics tools to visualize how customers use various channels in their journeys and the aspects of the multichannel customer experience that are working well and those that create roadblocks that can be acted on and improved.
4. Identifying the customer microsegments that drive the greatest long-term financial value. Every customer is different. Each has different needs, behaviors, and preferences. However, analytics can help CMOs uncover behavioral similarities between customers in certain categories (e.g. single mothers of teenage children; dual-income, empty nesters) and then craft personalized offers aimed at meeting their unique needs and interests.
5. Analyzing customer behaviors across multiple channels to determine how, when, where, and why customers are most likely to purchase. Big data and analytics can reveal powerful insights about customer behaviors in different channels. Depending on the products, customer needs and preferences, some consumers show a proclivity for buying certain types of products (e.g. consumer electronics) online versus in-store or via mobile. CMOs can use these insights to help direct targeted offers at select customer groups based on their past and anticipated behaviors.
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