Outlook 2016: How CRM Will Foster an Era of Good Feelings
CAMPAIGNS ARE BEING BUILT AROUND COMMERCE
While likes, clicks, and views can provide valuable insight, campaigns cannot exist in a vacuum. Rather, successful campaigns are being built around conversion and commerce, because regardless of how catchy, popular, or memorable campaigns are, they're increasingly being measured by their ability to bring in revenue. "The metrics that we've always talked about, like customer satisfaction, they're secondary metrics. The primary metric that’s driving all these campaign investments is conversion rate optimization," Wang explains.
Even social media, which has become a solid campaign tool but has historically been a wild card when it comes to tracking conversion and ROI, is closing the gap between campaigns and commerce. Over the past year, a number of social properties, including Twitter, Pinterest, and Instagram, have rolled out direct-response buy buttons to make their content "shoppable." The injection of commerce into the social environment is a reflection of the broader trend sweeping the industry, according to Wang. Thanks to integrations between marketing and commerce solutions from vendors such as Salesforce.com and IBM, as well as many of the social players, connecting campaign investments to revenue is a reality, even in the nebulous world of social media marketing.
What complicates the relationship between campaigns and commerce, however, is that it is far from linear. Thanks to the onset of the on-demand economy, campaigns can't simply end once a sale is made. "All that post-sale activity, the support, the installation, the ongoing products consumers may buy, especially in an on-demand subscription market, companies must continue to engage people. It's about renewal and subscription, and that changes how companies sell," Wang says. Understanding the cyclical nature of campaign to commerce and learning how to leverage it will be the next phase of digital business growth this year.
JOURNEY MAPPING IS MATURING THROUGH AUTOMATION
Customer journey mapping has been around for some time, but as the journey becomes increasingly digital, mapping it can become more automated, a key innovation. "We're seeing a transition from simply finding out what the customer is doing at every touch point to a more sophisticated approach where we understand the customer’s complete journey," Greenberg says. "This is a different concept, because individual touch points aren't siloed when you look at the combined journey. It's more accurate now."
Solutions such as Adobe Campaign, for example, enable users to view and track the entire customer journey and make real-time updates to campaigns based on the behaviors observed. The ability to make live changes is critical, because journey maps are only effective when they're treated as living, breathing things, according to Nancy McCrave, user experience designer at Catalyst, a customer experience marketing company. "Often, stakeholders see customer journeys as a one-and-done deal, but this is not the case," she says. "Companies need to continually follow through and iterate as they map the customer journey, and they need to be vigilant [about avoiding] experience rot," or the tendency to add too much complexity to a design, hurting user experience.
Despite the challenges, analysts are optimistic about where journey mapping is headed. Companies are starting to understand that customer journeys are "sloppy," and don't always fit into prebuilt categories and notions, Greenberg says. "We're still at an early stage, but we're in a place where people understand that we can't do it the old way," he adds.
BIG DATA ISN'T AS DAUNTING ANYMORE
In 2016, Big Data won't be as scary as it was just a few short years ago, analysts agree. The data is becoming democratized, and thanks to solutions that simplify analytics, more users throughout the organization now have access to actionable insights, according to Anne Moxie, an analyst at Nucleus Research.
"With accessibility up and costs down, the line between Big Data analysis and good old business analytics is blurring, and the same users are incorporating Big Data techniques, often without moving from their current solutions," she wrote in her annual trend predictions report.
The onus now is on vendors to keep up with a new breed of analytics-savvy marketers, salespeople, and customer service professionals. Predictive analytics alone, for example, are not going to cut it in 2016 and beyond. The next level of analytics rely even more heavily on artificial intelligence and machine learning, and while predictive tools can make guesses based on patterns, incentive-driven analytics take those predictions a step further.
If a consumer buys the same cup of coffee every morning, predictive analytics can draw the conclusion that tomorrow, that consumer will likely buy the same cup at the same time. An incentive-driven solution, on the other hand, can make a more sophisticated prediction, Wang explains, taking into the account the knowledge that this consumer is traveling and may buy the same cup but at a different time, or at a different location. Predictive and prescriptive analytics "power" incentive-driven analytics, but they improve upon existing capabilities by evaluating the context as well.