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Despite being around for decades, AI is currently one of the most popular topics in business with Gartner predicting that by 2020 AI will be a top five investment priority for more than 20% of CIOs.
Join Joey Moore, Director of Product Marketing and Greg Moore, Manager for Personalisation and Campaign Strategy of Episerver for a practical webinar on The 3 key ways to improve the customer journey.
AI is currently closing the gap between detecting patterns from large data sets and predicting intent (a role traditionally reserved for human marketers and merchandizers). AI-powered technologies are replacing the manual work traditionally completed by merchandizers to make product recommendations and marketers to make ad spend decisions. For now, AI will not completely replace all human effort, but it will dramatically improve the effectiveness of ecommerce teams that use it while enhancing the experience of shoppers who purchase from AI-centered ecommerce businesses.
The primary way AI has taken the online world by storm is by delivering highly personalized experiences shoppers desire. Using AI to personalize the customer journey is a huge value-add, and those that have implemented personalization strategies see sales gains of 6-10%, a rate two to three times faster than other retailers, according to a report by Boston Consulting Group.
Many ecommerce websites use AI-powered product recommendations engines to target and personalize which products are displayed to customers. A variety of machine learning algorithms have been developed by technology vendors (including Episerver) that alter the recommendations based on the stage or channel a customer is shopping in. For example, algorithms that prioritize top selling products may be used on a product details page while algorithms that prioritize complimentary products may be used on the cart and checkout pages.
AI-powered personalization tools are now extending into new stages in the customer journey such as personalizing search results on ecommerce websites to each individual shopper and injecting personalized product recommendations into new digital touchpoints such as shoppable mirrors. Personalized site search tools like Episerver’s Personalized Find automatically change the sort-order of product searches based on the behavior of the user who is conducting the search, which has the potential to dramatically improve relevancy of search results and lead to higher conversion.
But the most transformative AI-powered tools we will experience as consumers will use natural language processing (NLP) to understand and respond to voice and live chat interactions. NLP chatbots can be embedded and used through major messaging applications to act as customer service agents without needing a human. Chatbots make it easy and fast for customers to reach retail businesses using the same messaging services they use daily.
NLP voice commerce tools and virtual personal assistants (VPAs) will also transform how consumers interact with ecommerce websites, by allowing them to search and purchase using voice commands in scenarios where a customer doesn’t have a touchscreen or computer. In fact, by 2020, Garter Research predicts end-user spending on VPA speakers will reach $2.1 billion, growing at a compound annual growth rate of 43% from 2015 through 2020, while by 2018, 30% of our interactions with technology will be through “conversations”.
While AI has and will continue to transform how we shop online, the most revolutionary changes to ecommerce will be how online retailers and B2B companies analyze customer journeys and make marketing and merchandizing decisions. Predictive analytics will allow AI to take over discernment and prediction historically reserved for human judgment.
Predictive analytics uses pattern recognition technology to process and detect patterns in large amounts of data, often so large and diverse that many marketers and merchandizers would overlook them. Once AI can detect these patterns, AI programs can be taught to display these findings to merchandizers to act upon. This is called next best action. There are three scenarios emerging for ecommerce teams big and small to take advantage of when it comes to predictive analytics:
The technology that enables this level of analytics requires a centralized repository of all customer data including browsing behavior and purchases. In the emerging field of AI-powered ecommerce, data is the new currency. Ecommerce departments must centralize their customer and order data and enrich this data profile by integrating their marketing, ecommerce, and back-office technologies together. Some companies are years into these initiatives but most have not even begun. Episerver is piloting a Customer Data Management platform which will enable marketers and merchandizers to run predictive analytics use cases like the ones described above.
Advances in artificial intelligence have changed our lives and the impact of AI in retail and ecommerce is undoubtedly picking up speed. AI is starting to have a significant effect on the way ecommerce businesses attract and retain customers. A survey by Gartner predicts that by 2020, 85% of a client’s relationship with a business will be managed without interacting with any human. While ecommerce giants like Amazon, Walmart, and eBay have used these capabilities behind the scenes for years, more modest ecommerce teams can do the same, dramatically improving the effectiveness of the teams that use AI while enhancing the experience of shoppers who purchase from these businesses. AI is becoming more and more sophisticated by the day. And ecommerce businesses are now able to harness that power to improve consumers’ shopping experience.
Smart Insights are holding their fourth digital marketing Summit on the 12th December, where they will explore the key digital trends for 2018. Join Joey Moore, Director of Product Marketing and Greg Moore, Manager for Personalisation and Campaign Strategy of Episerver for a practical webinar on The 3 key ways to improve the customer journey.
In this webinar, you will learn the value of personalization to businesses. We show you how it can improve your customer's online experience by giving them an individualized journey resulting in improved satisfaction, increase loyalty and ultimately more profit to your business.
We will walk you through the 3 key ways and show real-life examples for each:
The importance and convergence of Analytics and Machine Learning
The three tiers of personalization - Basic, Segmentation, and Behavioural
How you can implement your personalization strategy by using:
- Personalized Search Results
- 1:1 Individualised Email Marketing
- Content Personalisation
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