There’s so much choice available that customers can pick and choose who they buy from and where, when, and how it happens. They want to discover, research, evaluate, and purchase on their preferred channel. Give them that option, and they’re more likely to choose you. That’s the whole point behind the multi-channel approach.
Social media insights are not only helping GE Capital’s Australian team better understand how customers relate to its products and services, they’re also driving more targeted, real-time marketing campaigns.
At the inaugural ADMA Techmix conference in Sydney last week, GE Capital’s social media lead analyst, Leigh Price, outlined several ways the B2B organisation’s recently established digital centre of excellence is actioning social media insights.
GE Capital is GE’s money and personal loans business. Price is part of a global pilot in Australia launched two years ago to trial a dedicated digital centre of excellence and build a social media analytics and insights capability framework.
Under the social media insights framework, Price’s team listens not just to mention of brands, campaigns and competitors on social channels, but also category discussion, individuals recognised as experts or influencer in the products space, and positive and negative drivers at a category level.
The data from these listening activities is then rolled into lead metrics, including qualitative indicators such as customer conversation, category conversation, brand conversation, competitor, as well as quantitative metrics, such as volumes, trends, channel split, share of voice, sentiment, influencers, and our own channel performance.
Example 1: Online shoppers
The first example Price shared of using social media insights on its 28 Degrees Mastercard was around expanding the product’s scope beyond its core travel audience. Through CRM data and card usage, GE knew some customers were also using the card for online purchases to avoid transaction and conversion fees.
“We sliced that data into the context of social conversations and how people talked about the card. We had a volume of people talking about the card only for online shopping, and a bunch talking about it for travel, and those neutral queries in the middle, which are mostly customer service queries,” Price explained.
“We were surprised at the high level of discussion about online shopping, and also surprised to find that when we segmented data, the positive conversations about the card were far stronger and exhibited more advocacy when using the card for online shopping, versus travel.
“Online shopping is also great for us as a business because unlike travel, which might be once or twice per year, online shoppers use the card on an ongoing basis.”
To target that audience, GE had developed automated lifecycle emails explaining the benefits of using the card for online purchases, but Price said it could see the opportunity to drive messaging further.
“We began experimenting on changing the message on social channels purely from pushing travel to talking about online shopping benefits. We also used social analytics to identify the most influential sources where people were talking about the card for shopping, and we targeted those sites with tactical ad campaigns,” he said.
As a result, GE saw the graph in conversations around the product spike when it started talking about the online benefits via social, Price said.
“We saw a big impact when we started changing messaging. That’s a great insight for us,” he said.
Example 2: Influencer knowledge
Another way Price’s team uses social insight is by uniting influencer data with Web analytics. He pointed out most analytics platforms include an influencer algorithm that shows the influence a user in terms of retweeting and sharing, along with blog sites and forums.
“This data can be good on its own, but where it gets interesting is when you mix it with Web analytics data,” Price said.
“When we were trying to change our messaging from travel to an online shopping discussion [with the 28 Degrees card], we used social analytics to split out blogs and conversations only talking about the card in a shopping context, then brought in Web analytics data to crossover the value of the conversion traffic each blog was giving us.
“We could not only see how influential each blog was, but also see the quality of the traffic being sent to us and the value it had.”
Through this activity, GE Capital could see that although some sites were more influential, there was a distinction between what generated brand awareness versus a direct conversion. Price said GE used this combined data to strike a balance between which influencers it endeavoured to reach out to, and getting quality conversion traffic.
Up next: Using social insights for real-time competitive response plus better understanding digitally savvy customers