AI driven innovations in Customer Journey Analytics

It’s amazing to see how brands are starting to incorporate AI insights into their businesses. The opportunity to use artificial intelligence as a catalyst for growth is immense. For example, with Adobe Firefly, brands can leverage generative AI for content creation to significantly reduce the time and effort required to produce high-quality content at scale. Forrester also discovered that early adopters are seeing benefits like cost savings and revenue generation from AI.

As with every new technology, incorporating AI solutions into your workflows can appear daunting. Adobe is making this easy and accessible in Customer Journey Analytics. If you’re not actively starting to use AI today, it’s time to start so you can reap the benefits:

1. Accelerated productivity and upskilling
2. Increased revenue
3. Improved customer sentiment
4. Reduced costs and overhead

Customer Journey Analytics surfaces insights when needed to empower all user types — both technical and non-technical — to augment user workflows to uncover insights, assist users to confidently engage with data, and upskill faster. AI and machine learning have been a key pillar of our analytics strategy for years allowing you to:

1. Enable non-expert team members with simplified embedded workflows.
2. Connect broader teams through shareable, relevant insights.
3. Empower the whole team with context and insights that have been traditionally isolated.

Here’s how some of the AI-driven features that we’ve recently announced in Customer Journey Analytics can be incorporated into your everyday analysis:

• AI Assistant. Part of Adobe Experience Platform, AI Assistant helps speed up your workflow across Adobe applications, including Customer Journey Analytics. AI Assistant in Customer Journey Analytics uses generative AI to answer data questions users ask in natural language, so they can get answers quickly, speeding up workflows like onboarding and encouraging continuous learning. Soon, AI Assistant will be embedded into your analytics mobile dashboard for executives to ask these same questions on the move.
• Time series forecasting. Businesses want to be able to look ahead into key metric trends so they can plan, budget, manage and allocate resources to take advantage of positive business changes, as well as alter the course of potentially less desirable outcomes. Time series forecasting helps users predict future values and ranges of metrics against time. For example, users can analyze multiple metrics simultaneously, into the future, to determine things like the number of people that will visit a store location or your website during peak hours next week.

• Intelligent alerts. Receive automatic notifications when anomalies occur in your data. Set alerts based on several criteria including statistically significant anomalies and percentage changes. With AI-powered anomaly detection, brands can now detect big events in their data, such as the peak time orders were received and which SKUs were sold.

• Intelligent captions. This generative AI capability provides high-level insights on the data being analyzed, to aid in comprehension of insights. This helps users who curate projects for business stakeholders, by taking away the need to manually add in context and insight. Natural language captions also help business stakeholders quickly focus on key insights instead of having to sift through the data to find a relevant insight. Intelligent captions will include new visualizations, such as donut, bar, area, line, and multi-line graphs to help to tell the story even better, immediately. Want to know how surge pricing performed last week compared to off hours? Just use intelligent captions.

Pick up these new AI- and machine learning-driven features today to see how you can incorporate them into your daily workflows for faster time to value.