From chatbots to augmented reality, more and more digital marketing agencies and organisations are taking advantage of artificial intelligence tools to create more personalised experiences for consumers and deliver higher conversion rates.
What is Artificial intelligence (AI)?
Artificial intelligence is the ability for computer systems to be able to perform tasks normally requiring human intelligence. Some examples include vision, decision-making and translation between languages. Most of these abilities use a technique called ‘Machine learning’. Machine learning is an application of AI that affords systems the ability to automatically learn and improve over time from experience without being explicitly programmed.
1. AI recommendations
You have probably experienced it as a customer of the biggest e-commerce retailer in the world as an ‘Amazon shopper’. Products are constantly recommended to customers on storefronts, while they shop and after they purchase. Amazon is the leader in the field of product recommendations, as it has finely tuned its algorithms to recommend products that customers are increasingly likely to purchase. Artificial Intelligence is becoming heavily integrated into the programs behind these recommendations. Amazon itself offers its recommendation technology as a product called Amazon Personalize through its Amazon Web Services (AWS) division, where customers can easily plug in their APIs into their e-commerce stores. Amazon Personalize utilizes machine learning to learn from its customers. This means programs can be fed millions of data points, such as customer actions; such as purchases, searches, location, age etc. and can then learn from this information to understand the behaviour of individual consumers and make predictions around what product they may like to buy next. The more data is put into these systems, the more they learn, and ultimately the better they become. These programs can learn from millions of customer interactions every minute. In the case of product recommendations that are marketed towards consumers, machine-learning systems can display increasingly accurate recommendations in terms of the likelihood for customers to make another purchase. Google has recently launched its own Recommendations AI platform (in beta) that is being offered to e-commerce stores as a standalone product as well being integrated into their own search platform, particularly in Google Search’s shopping tab where the best possible matches are recommended based on individual user’s behaviour.
Chatbots are fast becoming the go-to for direct customer interaction with businesses. Most larger-scale websites have adopted them as a ‘handy’ e-commerce assistant and they are prevalent on Facebook business pages and website support pages. However, many of these chat bots are often limited in their function, only answering to specific inputs, and providing limited prompts. Very often these Chatbots are simple in nature, just text-prompted software with limited capacity. People ‘talking’ with said bots can almost always tell they are not communicating with a human. AI-powered chatbots are different in that they use machine learning technology to create chatbots that respond in a more organic manner. The implementation of AI in this case allows for people to communicate with chatbots without any loss in comprehension as if they were talking to another human. Granted, the extent of this ability may not fully pass into all realms of conversation, yet in the more confined scenarios of digital marketing, they allow for direct customer communication with very little compromise. Bots such as Pandorabot’s ‘Mitsuku’, which has won the Loebner Prize Turing test a record five times, has been found to be almost indistinguishable from humans in brand-to-consumer communications. Brands can communicate in a one-on-one approach with every individual customer and can create a fully customized marketing experience to consumers, increasing connection to the brand. Furthermore, AI is being used to develop a natural sounding voice, as seen in Google’s text-to-speech products. Using its proprietary ‘WaveNet’ technology, customers who use Google’s API can train a custom speech synthesis using their own audio recordings, to create a unique natural sounding voice for each brand, with tools to finely adjust a voice individually. Brands can implement this technology with the powerful chatbots on an audio level, connecting consumers through audio calls almost undifferentiated from a ‘normal’ one-on-one conversation. This can allow for another level of immersion when marketing to individual customers on a personal level, creating more individualised experiences, as well as eliminating support wait-times. They can also assist the visually impaired who cannot traverse traditional visual customer support systems.
3. Customer Relationship Management
Customer Relationship Management (CRM) systems provide a generally centralized location where businesses can store and track all their customer descriptions and interactions data in order to create stronger relationships with their customers. Naturally, these systems deal with vast amounts of data and thus can be perfect for Artificial intelligence to make an impact. Salesforce have developed one of the most popular CRM systems for small businesses and international enterprises alike to use. Salesforce among close competitors has been implementing AI into its Customer 360 platform as part of its CRM system. In this case, businesses that use CRM systems are implementing computer accelerated learning, to allow these systems to dive down to the individual customer and create highly personalised profiles based on their relationship with the organisation. CRM systems are able to learn from each individual action and prepare possible procedures to take for customised customer groups. This is ultimately creating CRM platforms that are replicating one-to-one dedicated customer relations staff, however unlike their physical counterparts, this AI customer relation software can scale to millions of customers. These AI-enhanced CRMs can recognise what has been effective and even generate new leads and customer attraction/retention techniques based on what had performed well in the past or what is predicted to work in the future.
4. AR product placement
Augmented Reality (AR) refers to the overlaying of computer-generated perceptual information onto the real-world environment. Objects in the real world can be enhanced and built upon with virtual imagery or even audio, haptic, somatosensory, and olfactory displays. Most often, this technology uses smartphone cameras and displays to overlay information in the camera’s view, but it can also be used in ‘AR headsets’ which are goggles or glasses such as Microsoft’s HoloLens that can overlay information directly into a user’s field of view. AR uses an application of AI called ‘computer vision’ which refers to software systems that can recognise objects and scenery in video feeds. You might have seen this in forms such as immensely popular ‘filters’ seen on various social media platforms, where AI algorithms can recognise faces and apply AR overlays. Another popular implementation is the mobile game Pokémon GO, where players can catch AR Pokémon through their smartphone cameras. These techniques are being brought to the digital marketing world and are becoming particularly useful in a COVID-19 realm where customers cannot necessarily visit a store in person.
Companies are using AR tech to allow customers to ‘try’ their products, creating overlays of what their products would look like being worn by them or inside their homes. Adidas’ mobile app allows for customers to virtually ‘try on’ shoes, where the overlays a 3D model of the shoe onto a real-time video feed of the user’s foot, giving an accurate look as to how it would physically look. Similarly, Estee Lauder and Sephora are rolling out AR make-up try on features using ModiFace’s AI tech and Ikea have launched their ‘Ikea Place’ app which allows potential customers to place their furniture around their home virtually. These services are bridging the gap between search and experience goods, allowing for people to experience goods prior to purchase, something that holds immense purchasing power for potential customers.
5. Digital/social advertising
A culmination of AI technology tools are enhancing the already immensely powerful advertising instruments that the likes of Facebook, twitter and google have built. These services can record and analyze measurable impressions, click-through rates, bid levels, demographics and more, providing vast amounts of data. This data can be used to target specific customer segments, generating the basis for more efficient marketing campaigns. AI is being used to learn from this data and make predictions on what types of advertising may yield the highest returns. Yes, Humans have the ability to create and measure high quality advertising, and improve ads based on what they learn but the pure amount of data from a multitude of channels at scale is something that can only be examined by AI. AI-powered ad tools can identify patterns in advertising data, then predict what alterations to campaigns will enhance performance for specific KPIs. AI can even be used to visually evaluate successful ads of the past and help develop new ones that are likely to be successful in the future. AI tools for advertising such as Albert can automatically optimize advertising spend across various channels based on customized target audiences. Albert can even recommend and reach new target audiences that may not have been thought of by the user yet are predicted by the software to generate high conversion rates.
Overall, AI tools are proving to be immensely powerful and this technology is truly changing the digital marketing industry. Better yet, many of these tools are very affordable due to their automated nature and often provide free trial programs. There has never been a better time to implement AI technologies into marketing businesses.