The marketing and advertising technologies sector has experienced incredibly rapid change in the past few years. The pace of change is accelerating due to the proliferation of data across multiple channels, which enables marketers to build ever more precise profiles of their customers.
Marketers can now draw on data from search engines, social media, content viewing and more to understand what individuals are interested in and how likely they are to make a purchase. At the same time, the cost of analysing this data in real time has reduced dramatically as cloud service providers such as Amazon Web Services, Google Cloud and Microsoft Azure compete to attract customers to their huge data centres.
These developments combine to help marketers move ever closer to providing truly personalised marketing – an ideal which has been talked about for long but is now starting to become reality.
As a result of the abundance of data and the ability to process it cheaply and quickly, marketing personalisation has moved from crude lists of marketing leads based on age and wealth profiling, often inaccurate, incomplete or out of date, to real-time behavioural segmentation which predicts when the customer is most likely to engage positively with the brand or to buy the product.
We are moving ever closer to one-on-one marketing with fully tailored messaging, even bespoke content delivered at precisely the right time in the buyer’s journey to a sale. For marketers, personalisation is no longer a “nice to have”, because undifferentiated mass marketing doesn’t even reach the audience any more, due to ad blockers and spam filters.
Startup innovation
These rapid changes have given rise to a myriad of new startups creating innovative technologies that can aggregate and analyse data, build complex customer profiles and deliver optimised content in real time. Programmatic ad trading, where display ads are bid for and shown in real time, has been a reality for a few years. Through advances in natural language generation and processing, we are now seeing the emergence of personalised web site content creation and email marketing messages, largely created by machine algorithms.
Perhaps even more importantly, unlike previously used “if/then” rules based technologies, machine learning algorithms improve the results they produce over time, making them more relevant to the customer.
To illustrate how fast machine learning technologies are changing the consumer experience, consider the development of chatbots. Unlike many other areas of marketing, which remain hidden to the consumer, chatbots are very visible. Not long ago it only took a few interactions on a website to realise that you are conversing with a machine, rather than a customer services agent. However, most have now become so sophisticated, not just in terms of the accuracy of responses but also the style they use to deliver them, that it is hardly possible to distinguish whether we are engaging with a person or a machine.
Innovation and technological development continue to drive new ways of engaging audiences. Voice interfaces are one example. The advances made in recent years in the fields of natural language processing, conversation interfaces, automation, and machine learning and deep learning processes have enabled virtual assistants to become increasingly intelligent and useful (Siri, Cortana, Alexa).
However, using voice to interact with digital devices means that marketers have to change many established practices. Consider search advertising, a key channel for new customer acquisition. Almost one-third of the 3.5 billion searches performed on Google every day are voice searches. Voice search differs from desktop or mobile search using a browser. While browser search could give a long list of results, most voice assistants produce a limited number, often just one.
This makes search advertising either very efficient, if the brand is the only result appearing, or completely inefficient if the brand is not represented at all. Therefore advertisers need to develop new strategies for search engine optimisation, for example by using more conversational language.
One of the biggest trends in marketing over the past few years has been the use of video. This trend, which directly reflects how consumers prefer to engage with brands and media, is likely to continue for some time to come. Research shows that the use of video in marketing emails and on landing pages increases conversion rates dramatically. Live video is growing fast as a marketing channel and a number of platforms have emerged which offer brands and advertisers the ability not only to host video content but also to access a wide range of additional functionality around audience analytics, privacy and security and content recommendation engines.
Taking video a step further, a number of brands are experimenting with the use of augmented and virtual reality, which makes for a rich and immersive experience. IKEA, Starbucks and Volkswagen are just some of the global brands which have used AR/VR in brand marketing as well as for the sale of specific products.
A complex ecosystem
The marketing and advertising technologies sector is a large and complex ecosystem, and as such it is not without its challenges. Increased regulations around data privacy and usage require many companies to revisit their business models. The dominance of Amazon, Facebook and Google is a significant concern for many start-ups and many investors. However, challenges also create opportunities. Companies such as UCLTF investee Hazy are providing solutions that enable data analysis while preserving privacy and ensuring compliance.
In a world where consumer attention spans are reducing, advertisers are looking for new ways to engage with audiences, measure the engagement and deliver a better return on their marketing spend. This fuels innovation as start-ups are looking to provide new tools to help advertisers and thereby claim a share of a huge global market. Some of these new companies are delivering phenomenal growth and one day will become very large players. Others will be bought by the main marketing automation and social media consolidators, which continue to acquire as they expand their portfolios and client propositions.
In the past year, we have exited investments to Oracle (Grapeshot) and Facebook (Bloomsbury AI) and made exciting new investments in companies such as Phrasee, which uses natural language generation and machine learning to optimise short marketing messages, Black Swan Data, which uses predictive analytics to provide consumer insight to leading brands, and Convertr, a customer acquisition platform that optimises lead conversion and increases the return on marketing spend.
We see marketing and advertising technologies as a fertile area for investors and home to some of the most promising young businesses and ambitious growth stories in the UK.
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