How to Improve Your Targeted Marketing Efforts Using Social Insights
Over the past couple decades, an increasing number of business technology (BT) buyers have started to use social media. In 2012, more than 80% of BT buyers in the US and more than 75% in EMEA were seen to use social media for work purposes. As customers start to spend more time on these sites, the amount of social data available for companies to turn into actionable insights has increased as well.
How Cisco Uses Social Scoring
At Cisco, social data is the foundation upon which we derive our social intelligence. Social Scoring is a method by which we capture and process our customer and partners’ social interactions to build “virtual profiles” for each individual. Essentially, we aim to obtain a 360° view of each customer so that we can improve our marketing efforts.
There are many different types of scores, including topic interest scores (TIS), which reveal how interested contacts are in a certain topic area, and engagement scores (ES), which portray readiness to buy. Based on these scores, we’re able to better our chances of identifying potential leads and target customers with specific content that they’re more likely to respond to. For instance, we might assume that a customer with a high ES and high TIS for Collaboration has a high propensity to buy Collaboration-related products; thus, we’re more inclined to have a Contact Center sales rep actively reach out to this individual.
Behavioral Targeting Using Persona Scores
Another example is social persona scores. Based on Forrester’s Social Technographics Ladder, these scores take into consideration people’s activities on our Cisco.com properties such as Cisco Blogs and Communities. We are able to classify B2B tech buyers into overlapping levels of social participation depending on how they behave online. For instance, a contact who reads blog posts without logging in is placed in the socially passive “Spectator” group. Another individual who is more engaged and writes blog posts is placed in the “Creator” group.
We’re then able to target these personas with different content that resonates best with each group. According to Advertising.com, such behavioral targeting may help increase response rates somewhere between 300% and 2,000%.
As a first step, we set out to answer the following: do individuals in different personas react differently to online content? We segmented out the entire sample into 2 groups: socially engaged (including Creators, Conversationalists, Critics, Collectors) and socially passive (including Collectors and Joiners). Both groups were shown the same series of diverse banner ads on Cisco.com (see example image below). These banner ads included the following types:
- Analyst reports
- White papers
- Design guides
- Purchase offers
- Webcast recordings
We conducted initial analysis of click-through-rates (CTRs) with Adobe Test&Target for 128 live offers and found an interesting phenomenon. On average, socially engaged individuals have a 0.64% higher CTR for all banner ads regardless of the offer type. In particular, the design guide and purchase offer proved to be a couple of the more popular forms of content for the engaged group with a 2.26% and 1.81% CTR, respectively, compared to the less popular white paper which had an average CTR of 0.42%.
What can we conclude from this study? Perhaps we should be targeting more online content at our socially engaged contacts to meet their high level of online content consumption. In particular, perhaps we should think twice before creating another white paper and consider using design guides and purchase offers instead.
At this point, I’d say we’re only uncovering the tip of the iceberg, and it’s too early to make any assumptions. However, it’s clear that we shouldn’t be treating all customers the same. Social data is a tool we can leverage to gain more insights about individual preferences so that we’re equipped with the knowledge to serve our customers better.
I’ll leave you with one caveat. Despite the importance of integrating social insights into work processes, we should always be prudent in how we apply them. You may have heard about the story of how Target used social data to find out about a teen’s pregnancy before her father did and started sending diaper coupons to the girl’s home. You can imagine that wasn’t the best way for her dad to find out about the pregnancy. Let’s use this as a lesson to always make sure we are leveraging this information in a moral and appropriate manner while respecting our customer’s privacy.
How does your team use social insights? Share your thoughts in the comments section below.