In this article, you learn the importance of using artificial intelligence and machine learning (AI/ML). Next, review the benefits and real-world success stories from global customers using Virtual Analyst and Segment IQ to detect anomalies, avoid outliers, and maximize ROI.
Perhaps you recall the time chess champion Garry Kasparov was defeated by IBM®’s Deep Blue. Experts were convinced a machine could not possibly beat human decision making and judgment in a game as complex as chess. Yet, it was done and this was key to a fundamental shift in business strategy and technological innovation as the power of artificial intelligence was unearthed.
Adobe Analytics is the core system of intelligence for the experience business, enabling anyone in the enterprise to understand and optimize customer interactions with their brand across all touch points in real time and at massive scale.
Adobe’s AI tools are not here to replace you, but rather to enable you to achieve maximum ROI on your efforts.
To evolve your analytics, we must focus on three key considerations:
Organization - How to create holistic views of customers, prioritize insight-driven decisions and democratize data.
Technology - How to make sure that data and technology deliver personalization at scale.
Customer - How to build trust and adapt to change.
Analytics is challenging and time-consuming, yet there is a constant need to accelerate time-to-insight. Key issues organizations face include:
When it comes to a successful customer intelligence strategy, we need to move through three levels (see Figure 1 above) from: (a) data collection, to (b) data processing, to © analytics and machine learning, before we can finally take action and optimize our content and ads.
Data collection depends on your organization and may include various channels and mediums. These include OTT devices, video, enterprise, call centers, in-store, social email, web, ads, mobile apps, wearables, IoT, voice assistants, connected cards, and geo / spatial.
Data processing includes real-time data collection, processing rules, audience syndication, context-aware sessionization, real-time triggers and views, and platform.
Analytics and machine learning includes Segment IQ, Virtual Analyst, Segmentation, Analysis Workspace
Think of the Virtual Analyst as the rock star analyst who:
The virtual analyst uncovered the following scenarios for real Adobe customers:
Stay informed of anomalies within your data at all times - whether you’re in the office or on the move
Mobile vs Desktop: “We compared hits from one of our sites to another site and quickly found a bunch of tagging inconsistencies.” → Avoid data problems before a product release
Feature usage: “Customers who used our product comparison feature were 10% more likely to convert. Moving it to the top of the page grew orders.” → 4% increase in conversion
Content engagement: “We discovered that visitors to our news section were twice as likely to watch video ads, so we added more video options to that section.” → 7% increase in video ads viewed
Paid search: “Visitors coming from search engines were 3x more likely to upsell. We upped our spend on specific keywords as a result.” → 56% upsell lift
Product stock-out: “People buying Fitbits were 6x more likely to get an ‘out of stock’ than everyone else, so we quickly ordered more Fitbits.” → Stock-outs prevented and more holiday orders completed
For more information, watch our webinar.
Learn more about strategy and thought leadership at the Customer Success hub.