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10 reasons to bet your money on AI

Artificial Intelligence is all the rave this year.If you didn’t know this already, Artificial Intelligence is the ability of machines or computers to emulate human thinking or decision making.

Banking on this trend, Zenith has unveiled 10 trends that show how artificial intelligence will help to power the consumer journey in 2017, driving engagement opportunities and effectiveness for marketers. 

1. Predicting our needs: AI enhances the role of search in the consumer journey

Search is becoming increasingly predictive, providing tailored recommendations throughout the consumer journey to drive both consideration and conversation. During 2017, search engines will begin to factor in additional behavioural data – artificial intelligence technology will use this information to power predictive search. Enhanced predictive search gives clear opportunities for brands to better anticipate consumer needs in order to serve more relevant and also to cross-sell products.

How can brands take advantage of the trend?

This trend enables brands to better anticipate consumers’ needs based on the context of their search. Brands can help consumers focus and shortlist the products suited to the context. By understanding the context of their search, brands can also serve consumers with relevant content to help them make better decisions.

What are the implications for brands?

The consumer journey will become a much more dynamic entity both as a brand tool and as a real experience.

Humans will not become redundant in this shift.

Someone will need to make faster decisions to act on the implications of prediction at scale.

2. Speed is the new black: Turbo-charging the delivery of trend content

With data set to grow in quantity, machine learning will significantly help to streamline the process, digesting data from a variety of sources to quickly identify underlying patterns. Using AI in trend analysis will help marketers to stay ahead of both the trend curve and the competition. Content specialists will be able to create a pool of assets that can be quickly served to consumers in line with trend analysis, and product development teams will be better equipped to stay on top of the latest category demands.

How can brands take advantage of the trend?

This trend enables brands to stay ahead of the trend curve and to use fast-turnaround insights to inform product development and logistics. There is a great opportunity to stay ahead of the competition by setting trends and constantly surprising consumers with new products and designs.

What are the implications for brands?

The identification of underlying patterns from an increasing pool of real-time data will create enormous opportunities for content specialists to create stories and pools of assets that can be easily and quickly adapted. This speed of insight delivery will also create opportunities for product development teams, enabling them to stay on top of the latest category demands.

3. Always-on insights: Non-stop data collection through the massive user interface

The passive user interface continually collects behavioural data from consumers’ digital devices and by applying machine learning techniques can provide brands with powerful insights than can be used to customise consumer experiences.

How can brands take advantage of the trend?

The passive user interface will enable brands to better understand consumers’ usage of brand apps. In turn, this will help them to design personalised content and services and to set appropriate pricing strategies enabling consumers to pay in accordance with usage. In the future, with high adoption of Internet of Things, brands can also understand how their products and services are used alongside others.

There is also great opportunity for brands to collaborate across categories in order to design personalised services, or in the future even to cross-sell products.

What are the implications for brands?

The collection and analysis of more passive data will enable brands to negotiate more app-based data partnerships with complementary companies. Passive data on consumer behaviour could be shared and used across a range of categories such as health and well being, travel, music and fashion (with the requisite permissions of course).

The collection of passive data for well being brands will enable them to understand more about the context in which consumers use their products and services and allow them to offer customised advice. In fashion, passive data could enable fashion brands to connect moods with browsed garments, enabling them to tailor wardrobe suggestions to better suit consumer needs.

4. Cross-device storytelling: Advances in programmatic automate brand conversations

Machine learning technology is starting to help brands to tie their conversations to specific individuals. Brands have plenty of first party data, but this specific application of AI links individuals to their devices and helps brands to understand how consumer engagements and brand actions can be attributed to different messages in different contexts at different times.

Brands can then automate their conversations with consumers using cross-device programmatic advertising. This will really help to create seamless experiences, and to accelerate both purchase and re-purchase.

How can brands take advantage of the trend?

Cross-device storytelling enables brands to understand how and when consumers use their devices along the consumer journey, shape relevant content and provide seamless experiences to accelerate purchase or repurchase.

Providing consistent stories to individuals across different devices and properly attributing the resulting consumer sales or actions will help to drive ROI.

What are the implications for brands?

Cross-device communication can provide real and visible value to the consumer. The key for brands is getting to their customers and, through the trail of clues they leave when they visit stores and websites, to learn how their behaviour tracks from one connected format to another. Different devices offer different opportunities for creative design and audience engagement. The key is to experiment, test and optimise creative to maximise effectiveness. The way stories are told is changing. People like to go deep and they love the episodic.

5. Shoppable content: Buying direct from branded content enhances consumer experience

2017 will be the year of ‘shoppable content’: purchasing items directly from editorial and branded content. ‘Evolutionary algorithms’ can tweak and optimise content in response to consumer’s navigation, creating live content. Universal shopping carts recreate the functionality of e-commerce sites without consumers having to create new accounts or provide credit card details for each new site they visit.

This combination of technologies will enable brands and publishers to keep consumers on their sites rather than forcing them to go elsewhere to buy.

Brands will need to treat content as a compelling combination of text, images and interactive features that create a shopping experience.

How can brands take advantage of the trend?

This trend enables advertisers and publishers to keep consumers on both their owned sites and editorial platforms rather than forcing them to go elsewhere to buy. Today’s shoppers enter and exit purchase decisions at various points during a site visit, so content providers have to plan their strategies around a circular consumer decision journey rather than a linear sales funnel.

What are the implications for brands?

The key part of content creation is to drive more action; that means to make it instantly shoppable. Brands need to make the route from discovery to purchase as easy as possible.

Content creation is no longer only about relevant text. Rather, it has to be a great combination of visually compelling images and interactive features.

Turn visual content into a shopping experience. Brands will need to provide a great purchasing experience. Consumers are interested in the stock, ease of payment, prompt delivery and free returns. Brands must not only optimise the whole customer experience, but also emphasise it in their marketing and messaging

6. Smart VR: Brand opportunities as virtual reality moves to smartphones

Virtual reality is moving from the solitary world of gamers to the mainstream of consumers experiencing VR through their smartphones. Facebook and Twitter already have live streams that can be accessed using headsets attached to smartphones. The shift to smartphones and to mainstream applications will present brands with many marketing opportunities.

How can brands take advantage of the trend?

Virtual reality presents retailers with the opportunity to transform how people shop they can try out products without ever having to visit a bricks and mortar store. VR applications have the ability to eliminate customer ‘pain points’, elevate customer service, and create personalised customer experiences. The successful incorporation of virtual reality into retail also has the potential to vastly change the way retailers design the stores of the future.

What are the implications for brands?

To build a business case for virtual reality, brands need to determine what users expect from a VR experience, and ascertain whether this meets its needs given the price of production, consumer demand, relevancy and point of entry. They should produce VR content for mobile consumers on the go and strive to make this content link up with the in-store experience to create a consistent consumer journey.

Brands must think about the big picture and virtual reality should be treated as part of larger marketing campaigns, rather than one-time events.

7. The rise of the chatbot: All hail frictionless communication between brands and consumers

Powered by machine learning, chatbots enable automated interaction between consumers and brands via a messaging interface. While there are obvious limitations with automated communication, chatbots can help consumers with process functions such as making payments and notifying of delivery/shipping. Chatbots can help brands to reduce customer support costs and to open up greater dialogue with consumers. There is also a great opportunity for brands to create personalised recommendations for consumers based on insights from the trails of chats.

How can brands take advantage of the trend?

Virtual reality presents retailers with the opportunity to transform how people shop – they can try out products without ever having to visit a bricks and mortar store. VR applications have the ability to eliminate customer ‘pain points’, elevate customer service, and create personalised customer experiences. The successful incorporation of virtual reality into retail also has the potential to vastly change the way retailers design the stores of the future.

What are the implications for brands?

Before brands launch their own bot experiences, they first need to determine who they are trying to reach and define the precise vertical (commerce, content or service) that the bot will operate in.

It’s important to limit the scope of what your chatbots can do by focusing on a particular product or service to start with.

Then, slowly expand the chatbot’s knowledge base by feeding it more relevant information over time. Remember, put the customer first, understand their intent and build new skills to address their needs. To provide a good user experience, a bot needs to have a good user Interface, as well as have the intelligence to conduct twoway conversations with a wide audience in real time. Use the data obtained from these interactions to further refine the chatbot and improve the products and services it supports.

8. Playing to our emotions: Emotion recognition technology helps brands to tap into human truths

The spread of smartphones and the rise of embedded emotion recognition technology means that many people now carry mood-sensing devices in their pockets. This gives brands the opportunity to match consumers’ moods and behaviours with relevant content at the right moment.

How can brands take advantage of the trend?

Emotion recognition technology enables brands to make more emotionally relevant recommendations and create customised narratives that evolve depending on viewers’ reactions. This technology will also help programmatic advertising become better at maintaining user engagement. As advertising becomes more automated, emotional recognition technology allows brands to personalise the way that content is served to consumers.

What are the implications for brands?

There many different applications for emotional recognition technology. This could work for brands that are cherished by a nation as they could aggregate and visualise the national emotion at key points in a country’s calendar and serve content accordingly.

9. Dynamic pricing: Algorithms enable automated demand-led pricing

Driven by high-performance computing and analytics, dynamic pricing enables retailers to price items at a point determined by a particular customer’s perceived ability and willingness to pay. Pricing on some website and apps now changes from minute to minute. For example, Uber introduced its surge pricing algorithm to enable pricing to automatically rise at times of peak demand.

How can brands take advantage of the trend?

Dynamic pricing enables brands to customise prices for consumers, ensuring brands get the most out of each customer interaction. It has the potential to widen profit margins considerably for those retailers that can implement it effectively.

What are the implications for brands?

Brands must ensure that their pricing reinforces their desired brand-value proposition with their target shoppers. If a brand is not a price leader, constantly changing prices can detract from their brand and erode their relationship with shoppers.

Use price comparison and monitoring tools to understand competitors’ pricing strategies. Brands should identify which product categories and audience segments are price sensitive, how often prices change for top sellers and sought-after items, and which discounts have been successful in the past.

 10. Automated assistance: service robots hit the high street stores

Industrial robots have been in use for many years. Now, technology is blending physical and digital automation to create service robots, working alongside humans.

The most obvious and immediate opportunities are in retail and hospitality.

Service robots will be able to provide pricing and stock availability information and using algorithms will be able offer discounts and related product suggestions. The opportunities could stretch beyond retail and hospitality into healthcare and domestic help.

How can brands take advantage of the trend?

Service robots open up room for top quality customer service in retail, hospitality, healthcare and domestic help. These robots are able to improve productivity and efficiency with quick and easy access to information to address customer queries. Allowing the service robots access to the right amount of data can offer customers real-time personalisation that may not be possible via a human.

What are the implications for brands?

Some industries are more relevant than others for service robots. Brands should consider the role of service robots in the service chain, how they work alongside humans and level of interaction with the customers. As a start, partner with robotics experts, AI experts and tech partners to find out how service robots can work to address current customer service problems and rethink how the service robot can shape a better customer service.

Brands will also need to consider how the robots can navigate the environment. Most importantly, brands need to manage customer expectations on how the service robots can assist them.

Zenith

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