3 Biggest Takeaways from Adobe Summit 2019

Adobe Summit never ceases to amaze and inspire us, and we’re so glad to have participated as a sponsor and partner last week in Las Vegas. Right from the opening keynote, it was clear that creating outstanding customer experiences was the primary focus of the event and that data was the foundation for providing those experiences. Adobe announced a host of new products and features which clearly demonstrate the importance of data in today’s marketing environment. After an intense few days on the ground, we’re boiling down the top three takeaways for Experience Makers.

1. Adobe joins the CDP ranks (Salesforce too)

2019 is the year the customer data platform is going mainstream. Adobe announced global availability of their Experience Platform which includes a real-time Customer Data Platform. Not to be outdone, Salesforce announced that it too had plans to build a CDP. This is big news for an already crowded field, and this obviously has huge implications. Big brands like Best Buy, Home Depot, Verizon Wireless, DXC Technology, and Sony Interactive Entertainment are already using Adobe’s Experience Platform in beta.

Adobe establishing itself with real-time CDP capabilities (which, it’s fair to say, still remain to be seen), validates this category which has been struggling to prove itself over the last two years. Current CDP vendors face an uphill battle now that these two giants have announced themselves.

It’ll be interesting to see how customers respond to Adobe’s platform. In our conversations at the event, we heard a few Adobe clients question the idea of sending their data outside their own firewall. It’s one thing to put your marketing data from SaaS systems into the cloud, but it gets a little trickier when you’re sending sensitive customer data outside your enterprise-controlled environment.

2. New tools for AI

Adobe has two approaches to AI. The first, and most prominent, is their Sensei platform, which provides out-of-the-box (some might say black box) AI and machine learning for customer experiences. Sensei is being built into every product that Adobe offers, from photo editing, to segment creation, to product recommendations. The second, not quite as prominent, is their Data Science Workspace, allows data scientists to build their own custom models using a notebook.

In the conversations we had, many Adobe clients were very interested in Sensei and felt that out-of-the-box models would suit their needs. Still, a few felt there is more value in building custom models. And while some of them were interested in a notebook solution, others were interested in a platform that would allow them to build and deploy dozens of models to production quickly and simultaneously.

3. A ton of interest in AI, but not enough action

In all our conversations, one thing was clear; everyone is interested in how they can use AI to transform their marketing data into intelligent experiences. It seemed that every visitor was curious how AI could help them and every vendor had a story.

Less clear, however, were concrete examples that have been deployed in the real world. Here at Syntasa, we’re lucky to have amazing clients, including Dixons Carphone, Sky, NowTV, The Telegraph, and Lenovo – all of whom are willing to share their real-life stories.

Resources to explore:

• Dixons Carphone is using Syntasa to architect customer data and deliver personalized bundles on the Currys PC World and Carphone websites. Watch this video and read the Dixons case study to discover the journey they’ve been on and how they have achieved a 3x improvement in add-to-basket rates.
• Sky is accelerating its personalization and analytics, combining Syntasa’s AI Assisted data platform with the Adobe Experience Cloud. Watch this video to hear how Sky’s Analytics and Insights team is unlocking the power of Sky’s marketing cloud to deliver incredible cross-channel experiences.
• Lenovo’s business analytics team has relied on Syntasa to simplify complex datasets retrieved from various sources and make them actionable through the application of customized machine learning algorithms. Watch this video, featuring their Head of Global Ecommerce Analytics, and read the Lenovo case study.