By: Steven Rahman
As we celebrate the 25th year of CRM applications and platforms, the emphasis of CRM is no longer on emails and physical addresses. Today, mobile is where customers are and IoT devices are soon to follow. Are CRM systems prepared for an era that might focus on device IDs, Data Management Platforms, and inferencing engines? On the cusp of CRM’s silver anniversary, what might we expect to see for CRM in 2017?
1. App fatigue is here to stay. As of March 2017, almost no productivity and business apps are at the top of the charts in app stores. Despite the proliferation of apps, as of June 2016, there were only 133 apps with an audience greater than 5 million users. Walt Mossberg of Recode recently deleted half the apps on his phone and wrote, “just as there are too many confusing, often redundant choices on the breakfast cereal shelves at the grocery store, there are too many duplicative and puzzling choices in the Apple and Google app stores.” Clearly, it’s time to rethink your CRM strategy if it includes a customer downloading an app.
2. 2018 will be the year CRM meets data science: Mobile first or mobile only Internet users will grow from 40 million in 2017 to 47 million by 2019, according to eMarketer. As consumers increasingly expect personalized mobile experiences, email campaigns have to evolve to reflect location data, context, and behaviors. Any CRM solution would benefit from an inference engine that makes real-time assessments of how best to connect to a customer and recommend content.
3. Solve the abandoned shopping cart: Barilliance, the eCommerce specialists, estimate that 78% of mobile shopping carts were abandoned over the 2016 Black Friday weekend (compared to 68% for desktop users). This means that $3.5 billion in product was browsed and selected but not purchased. The most common reason that mobile carts are abandoned is negative consumer reaction to unexpected shipping costs. In these cases, CRM systems should be prepared to receive the mobile signal and respond accordingly.
4. Close more sales by focusing on device IDs: If users don’t want to download apps or register with ecommerce sites, how can they be tracked down to offer a free shipping coupon? The ideal CRM system will be able to detect device IDs and match them with CRM information that includes a phone number, email, and home address.
5. Retargeting on mobile is unique: When marketers retarget with emails sent to desktop users, they experience conversion rates of around 20%. On phones, that number drops to 14%. For any mobile retargeting campaign, marketers should consider investing in a platform that takes into account mobile behaviors and context and can reveal when conversion probabilities are highest.
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6. In the mobile world, location data reigns: Retailers have discovered the importance of mobile user location. Urban Outfitters sought to leverage geolocation data over the 2016 Christmas season. They successfully “boosted customer conversions by 75 percent and increased related revenue by 146%” according to Geomarketing.com.
7. The European Union’s General Data Protection Regulation (GDPR) will come into force in 2018. The intention of this regulation is to harmonize data protection laws across the European Union. The regulation requires companies holding the data of European residents to comply with a very extensive set of rules around where the data is stored and how it is used. This means that companies storing user data in CRM systems must have an information architecture in place that makes it possible for them to reach customers while also proving to regulators that the data was handled properly.
As CRM turns 25, we find ourselves in a mobile first world. CRM programs should be capable of understanding their customers across a range of channels while also protecting user privacy, especially in Europe. But holding customer data could become a relic of the past. Much more is revealed about customers through on-line behaviors and context, all of which can be captured and processed by the right customer data solution and an inferencing engine.
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