How Artificial Intelligence Can Make Your Marketing Strategy Work

Financial marketers can take advantage of the recent developments within AI to ensure their efforts are executed in a more accurate and efficient manner. Integrating the power of AI into your marketing strategy can ensure your budget is spent in the right areas and your reporting is meticulous. There’s a lot to think about, so grab a coffee and let’s get to it.

For years, we’ve been hearing about artificial intelligence (AI) and more recently machine and deep learning, but what does it mean and how can it be integrated into your marketing strategy? Well, to start off with, AI can be defined as allowing a machine to carry out human tasks in a ‘smart’ way. A report released by PwC stated that AI could add around $15.7 trillion (roughly the output of China and India combined) to the global economy by 2030. With this in mind, it’s worth spending some time to break down what AI really is and how you can integrate it into your marketing strategy in the best possible way.

Machine learning
The terms AI and machine learning can often get confused with one another. Machine learning refers to a machine which can access data and facilitates a process for it to learn for itself without being programmed how to do so. Machine Learning is an important aspect of AI and is needed to make it work efficiently. No human can match the level of responsiveness that machine learning can provide. Algorithms are created to operate on data being received which is then used to forecast future outcomes. We’ve seen glimpses of its potential, but mostly, it can be used to develop simulations to predict how specific campaigns will perform based on previous results. Predictive analytics can identify and target visitors who exhibit the same behaviour as visitors who are known to have a high lifetime value (LTV).

Opportunity mining
But marketing managers shouldn’t run for the hills just yet. There is a lot of marketing automation software available which makes the day-to-day running of a marketing department more efficient. If your marketing strategy is your driver, popping you on the green, then AI is your putter, bringing the money home.

To get a glimpse of how AI will transform and enhance business productivity we need to understand how to combine the advantage of humans with the power of technology. AI in marketing it is often heavily focused on predictive analytics – give customers what they want before they know they want it. But this is just the start. Some examples of how AI can be integrated into your strategy are to include advanced data analytics tools, social media sentiment analysis, retargeting, lead scoring and speech recognition.

AI vs. human behaviour
AI is causing huge interest and excitement in the market but can the creative intelligence from humans which includes the ability to be emotional, sympathetic and flexible be outdone by AI which basis its decisions on logical, algorithmic and programmatic orders? Well, the answer is YES. The human brain encounters cognitive biases, which are systematic mistakes when we make decisions. This can include stereotyping, selective perception, information bias and overconfidence. These, amongst others, are reasons why using AI to support decision making outweighs relying on human behaviour alone.

Using AI to enhance your customer experience
Companies which aren’t integrating AI in order to improve customer experiences are going to be playing catch up. Humans can make mistakes as a result of not analysing complex data correctly. AI software comes in here to improve a marketing department’s productivity, save time and streamline a team’s efforts.

In line with data collection and security, it’s worth mentioning GDPR which is a new EU data protection law that will come into effect on 25th May 2018. This is early innings, but in a nutshell, it will require companies to change the way they store and secure personal data of individuals. It’s not exactly clear how things will change for CMO’s but it’s important to continue to observe announcements about how this will allow data to be used for marketing purposes, and especially how it is being stored securely.

AI and the future of the financial services industry
Strategic investment in the right type of AI technology is needed in order to make it work for you. Brokers need to be open to innovative approaches and task restructuring across all departments. We all want to gain a deeper understanding of our customer’s profitability to ensure we spend our budget in the right areas. For brokers wanting to develop their product offering, they can use AI to gain a better understanding when making performance-based decisions and being more transparent in their reporting. Profit and loss data can be collected and analysed to support decisions about budget allocation towards customer acquisition and/or retention.

The finance industry is becoming ever more turbulent and is rapidly evolving, meaning your customer support needs to stand out from the competition. To get a glimpse of how AI will transform the financial services industry we can look at the compliance procedure every broker needs to go through. AI can help filter through applications and speed up compliance checks; this kind of support is invaluable in a regulatory environment which is constantly changing and becoming more scrutinous.

Using AI to make everyday marketing better
Chatbots are definitely game-changing. According to IBM, Chatbots for customer service will help businesses save $8 billion per year. Automating conversations is becoming the new norm and humans are becoming more and more comfortable conversing with technology. Chatbots are conversational interfaces which can reduce knowledge leakage by using natural language processing (NLP) technology to communicate with customers. The technology is capable of producing logical, coherent text and stores the most common questions and answers being put forward to a client services department or a sales rep. Gartner’s recent study stated by year-end 2018, a customer digital assistant will recognise individuals by face and voice across channels and partners.

Another way NLP can be used within financial service is to give more meaning to numbers. By taking massive amounts of repetitive data we can request the most important figures be extracted and organized into a manageable report or executive summary which is easier to understand and to use to make accurate decisions.

The voice search revolution
There is no question that in 2018 voice technology is going to disrupt the way people search for companies and products. Matt Bush, director of agencies at Google UK stated “Our research shows that a staggering 75% of consumers said they search more now they can use voice search, while 83% of consumers agree voice capabilities will make it easier to search for things and 89% believe voice will enable users to find things more quickly,” But how do you optimise your website for Voice Search, i.e. spoken voice commands instead of typed words? If you already have SEO best practices in place then you don’t have to change much as Google recognises voice search queries in a similar way. Just make sure you don’t hide any answers in images and keep them in HTML as you want to make it easy for Google. In terms of site structure, you should keep in mind that when customers use voice search they are usually looking for answers to specific questions, for example, your address and telephone number or a particular product offering. You should structure your content to make it easy for Google to crawl your website to find the answers to these common questions. It might seem time-consuming and simple but try preemptively answering some questions to see if Google manages to find the answers.

Another way to leverage AI in everyday marketing campaigns is to collect and correctly analyse the information which is already present. Marketers don’t need a degree in mathematics to be aware that subscriber data used correctly will help send targeted and relevant emails. People are bombarded with content everywhere they go. The marketing strategies which will be successful in the long run are those that use this structured and unstructured data and turn them into insights to provide customers with a personalised experience delivered in a language that suits them, at a time convenient for them.

Whether you want to boost sales or optimise new leads, there are many ways in which powerful customer behaviour information collected from your website analytics can be used to trigger campaigns. Highly persuasive personalisation can be achieved by looking at the time users spend on a webpage, specific movements and drop off rates (especially on an application form). Once this data has been collected and stored securely it’s easier to create a customer segment and remarket relevant content. Gartner predicts, “By 2018, 20% of all business content will be authored by machines.”

To conclude
What if each time a customer contacted your company, you had a system in place which remembers the trader’s entire history of interactions with any company representative, trades placed, common behaviours, preferences and timings? This would allow you and your team to have more intelligent conversations and avoid going over often repeated processes, conversations or problems.

Ray Kurzweil, Google’s Director of Engineering, said that in just over ten years “singularity” (when artificial intelligence exceeds a human’s intellectual capacity) will come into effect. But he’s not worried, explaining “What’s actually happening is [machines] are powering all of us. They’re making us smarter. They may not yet be inside our bodies, but, by the 2030s, we will connect our neocortex, the part of our brain where we do our thinking, to the cloud….. we’re going to be funnier, we’re going to be better at music. We’re going to be sexier. We’re really going to exemplify all the things that we value in humans to a greater degree.”

A marketing campaign involves coordinating many different responsibilities and tasks. It would be impossible for one AI to take over every aspect of a marketing campaign without human interaction. Tasks that require less emotional judgment are increasingly susceptible to machine learning. AI can help companies tailor products to each individual customer by incorporate real-time data into actionable insights within the marketing material the customer sees.

In the near future, AI will affect almost all areas of a marketing strategy to a certain degree. Without the integration of AI traditional marketing models will soon not be worth the paper they are written on. With this said, if done wrong AI can cause operational, financial and legal damage as well as affecting a company’s reputation to ensure you have a dedicated team to decide how and when to implement AI.

Monetising Mobile Marketing

The number of regulatory changes, modifications to marketing guidelines and new players appearing in the market can make it hard for any business owner to figure out what to place their main focus on. According to comScore data released in June 2017 the total digital population is 254 million people. From this number mobile usage has suppressed desktop usage as a digital platform to access information.

With consumers accessing information from many different devices it has never been more important to tick all these boxes at the same time:

1. reach the right leads
2. in the right place
3. at the right time
4. on the right device
5. with the right message

A recent study from Google suggests 65% of British citizens access the internet from their smartphone.

Device Graphs

A device graph gives a comprehensive view of customer’s digital media and advertising behaviours. When working on Pay Per Click (PPC) advertising campaigns for example it is important to remember user behaviours when deciding which devices to target. An employee might be more active on a desktop during traditional working hours but then transfer their actions to tablets and smartphones in the evening. When it comes down to appealing to investors, mobile becomes unquestionably important no matter if the client is using an iPhone, iPad, Android or Windows Phone. Innovation in technology and connectivity are making digital experiences a more seamless part of investor’s everyday activities. Investors are more and more frequently willing to engage in high-value trading transactions and banking on smaller screens. According to Business Insider UK, Lloyds Group, Barclays, and the Royal Bank of Scotland (RBS) added 8 million, 5.7 million, and 4.2 million more mobile banking customers in 2016.

It is becoming harder and harder to stand out in crowded media platforms especially if a firm is trying to connect to investors globally. Therefore, ensuring the client is reached on their preferred device at the best possible time is essential in any communication strategy.

Will AI Marketing be the Next Data Revolution?

Getting the answer to this vital question will prepare marketers for success as they build strategies to incorporate Artificial Intelligence Marketing (AIM) technology into their businesses. Artificial Intelligence (AI) can simply be described as work exhibited by machines, rather than humans. Sophisticated, multi-touch advertising attribution is possible today and marketers are only now beginning to understand its power.

Data, Data, Data  
Thanks to software that can gather everyday surges of user data, 2017 has been the year that digital marketing statistics gain the credit they deserve.

A report by BlueVenn, states 72% of marketers consider data analysis to be the most important skill to acquire in the next two years.

With the correct technology in place actions on websites and apps can be carefully analysed, tested and continually improved. Targeted personalisation should be developed in real time, meaning the continuous modification of app notifications outside of their release cycles. Whilst it’s important to continuously gather insights from website visits and client behaviour, identifying things like the length of time spent and drop-off rate on each field of the application form, as well as the conversion rate on different devices and browsers is necessary. From there, it is possible to modify and re-test different forms to optimise the experience.

Predictive Analytics

Predictive analytics has gained an important seat at the table in 2017 as it identifies and targets visitors who exhibit the same behaviour as each other as well as visitors who are known to have a high lifetime value (LTV). Creating a visitor profile based on arrival data, site footprint, and customer data provides rich information that should not be neglected. Suppose, for example, a high LTV customer has entered the site from London using the keywords ‘best interest rates’ and has had six sessions, 30 page views, and we know from a half completed form that he’s 35 and married. Matches can then be created based on similar visits to prioritize product related messaging and promotions for these those visitors with a predicted high value.

Suppose, for example, a high LTV customer has entered the site from London using the keywords ‘best interest rates’ and has had six sessions, 30 page views, and we know from a half completed form that he’s 35 and married. Matches can then be created based on similar visits to prioritize product related messaging and promotions for those visitors with a predicted high value.

Throughout the lifetime of a client’s relationship with a company, they will be involved in many different touch points.

Usually, it’s the ‘last-touch’ (the final stage before a client converts) that has value attributed, although there a many more sophisticated attribution models out there.

In 2017 we’ve seen advances in technology allowing marketers to track multiple data points including social media channels, websites, landing pages, email campaigns, mobile apps and payment methods – all accessed from different devices. On average homes in the UK have between seven and ten devices connected to the internet at any one time. If there is a strong understanding of the overlaps across these platforms, these advances allow for clear demonstration of the ROI of each campaign and the channels used to promote them.

A user should be able to switch from their different devices and still be at the same point where they left off. Correct measurements will help a marketer to understand which channels are most powerful. Ultimately, being able to track an advert served across different devices and justify that it has actually achieved its campaign objective is paramount.

AI Marketing – Turn Data into Opportunity

This has been the year that technology advancements have changed the way digital users interact with brands. Artificial Intelligence (AI) technology can take some credit for this. AI can, in its simplest form, be described as work exhibited by machines, rather than humans. It is one of the most reported trends in today’s accelerating technology marathon.

Companies keep looking for the ‘next big thing’ and AI seems to be it. As it becomes more integrated into companies worldwide, it will be the driving force behind gathering consumer intelligence in the coming years and marketers should quickly adapt their approach in order not to be defeated by adaptive analytics and machine learning.

AI is gradually being integrated into various divisions in larger organisations from client services, sales, and marketing departments in order to improve the overall client experience offered to customers. Smaller companies might find it hard to adapt at the same pace but those who do not will likely find themselves losing out.

AI can make marketers conduct more intelligent conversations with their clients by connecting cross-channel conversations in real-time, matching their needs and finding solutions for their problems. AI technology has become highly sought after in order to reach clients and interact with them in their language. Innovative technology can predict clients’ preferences as well as find relevant solutions for their problems, sometimes even before the clients know what their own problems are!

While Artificial Intelligence is the buzz phrase for 2017 some seem to be forgetting what’s really important: maintaining superior client relationships. Most relationships have traditionally been conducted via email and telephone; however, in 2017 clients are expecting to be able to choose their communication methods to meet their daily digital behaviour. To stay ahead of the game companies must engage with each customer on a one-to-one basis. Having SMS, email, WhatsApp and web-messaging channels such as Skype, FaceTime, Google chat, WeChat and Viber linked together in one CRM, is an advantage to those willing to adapt. A marketing department should be able to combine data from all these touch points and streamline them into a powerful CRM system for a comprehensive client overview.


Finally, there is one fundamental element that will never change regardless of technological developments: the end customers. AI will definitely support the end customer as it will enable marketers to further spend time helping them in the most relevant and personal way.

Social Media for Financial Services

Social media has been considered superfluous by many players in the financial services industry, however, in recent years we have seen many companies reluctantly adapt after witnessing high levels of penetration, use, and engagement from consumers of all ages. New channels such as Instagram, Snapchat or Facebook’s Livestreaming, to name a few, have been key focus areas and will continue to show importance for the rest of 2017. Many marketers now have social media influencers as part of their marketing strategy; to easily and quickly convince and reassure consumers of the brands strong market presence. An Influencer has over time established credibility due to their interest and interaction in a specific industry. With their following comes the power to persuade a large audience simply because of their authenticity and access to thousands of other social media profiles.

Social media is now also being used to communicate with companies and is no longer a medium to simply market and communicate. A study conducted by Twitter demonstrated “when a customer Tweets at a business and receives a response, that customer is willing to spend 3–20% more on an average priced item from that business in the future”.

The new generation favours fast-paced technology due to being raised in social media and modern technology communities. This increases the demand for applications characterised by fast technological performance. With social trading, online influencers and social opinion polls it’s time to innovate and respond to customers in the same way they connect with each other. Due to the rapid evolution of peer-to-peer reviews, social media can be used to surface links to read positive evaluations of a trading experience from other clients in the same city trading similar products.

The impact of social networking websites will significantly push the technology revolution to continue growing and have an impact on our everyday lives. With all this in mind, and considering the highly regulated industry marketers work in, controlling the messages being posted and protecting the brand image should be at the forefront of any social media engagement strategy. The applications used for linking smartphones to TV, computer screens, smart books and other electronic devices will mean that social media presence in peoples homes will continue to be strong for years to come.

The biggest takeaway may be that without using social media for re-targeting, customisation and analysing data correctly, social media marketing can’t compel like it used to. Mobile, personalisation and contextual marketing are all vital parts of a successful social media marketing strategy, each promising a better ROI when implemented correctly together.


Why all Touch Points Need to be Considered

Marketers shouldn’t assign full purchase behviours to a “last-touch” campaign

Lead attribution is a method to add value to every campaign that influences a lead to finally buy the company’s products. For instance, if the marketing team introduced a new product to a potential customer, and the customer comes across an article from a search engine talking about this new product, then, he/she may return back to the company’s website to complete the purchase. The client might download a brochure and then come back to buy the product. Which campaign or touch points should the marketer give the credit for the sale to? They shouldn’t assign the full-purchase to the last-touch channel only. Analytics should be used to look at the customers complete activity and history.


Various stages of a marketing campaign should be analysed in order to give the appropriate campaigns and touch-points full credit. We should not forget top-of-the-funnel campaigns that pushed the buyer to ultimately purchase a product. A marketer should assign certain aspects of the purchase process to every campaign the buyer experienced before completing their purchase.

Which campaign has the highest-value customers?

The ratios are up to the company. If a client purchases for USD 8,000 and touched four campaigns before purchasing, the marketer could choose to:

• Assign proportional credit to every campaign. It depends on how far away it was from the buy point: 10% (USD 800 credit) to the first-touch campaign, 20% (USD 1,600) to the second campaign, 30% (USD 2,400) to the third campaign and 40% (USD 3,200) to the last-touch campaign.

• Give similar credit to each campaign (20% or USD 1,600 of credit to each campaign).

• Give a full-credit to each campaign (100% or USD 8,000 of credit to each campaign), as this campaign resulted in USD 8,000 in bookings.

Finally, the issue is not solely about which campaigns pushed potential clients to purchase the company’s product, but it’s mainly about how much they purchased. A marketer could take five customers spending USD 10,000 each over 50 customers spending USD 300 each. Which campaign has the highest-value customers? Every lead is valuable, but marketers usually want to know which campaigns created the best leads, and the most significant point is: how much money the company earns of these customers’ purchases?

Why Contextual Marketing Should Still be Your Top Concern

We get flattered when we walk into our building and the concierge knows our name, or when the local supermarket attendant asks how you have been as you haven’t visited for a while. Why should it be different when we target people using digital channels?

Every marketer should be able to answer this question, as Contextual Marketing aims to value clients by offering them the most relevant message at the most significant time and place. In order to know how Contextual Marketing will help create more beneficial marketing programmes; firstly, one needs to define it. In its most simple form, Contextual Marketing is all about relevancy. Marketers have to deeply understand this concept and take advantage of the ability to be able to send messages at the most critical moments, predict certain behaviours and communicate with customers in the most appropriate way.

It used to be considered clever when we personalised emails by addressing someone by their first name in an automated email. Times have changed and a well-structured Client Relationship Management (CRM) tool allows a comprehensive customer overview to be generated. With the incorporation of all touch points, to collect customer data, the CRM can provide an accurate understanding of the leads origin and behaviour. This can then be the jumping block for a brand to accurately monitor how a relationship starts and how communication should continue with that client.

Have you ever thought about how caught up you are in your industry and its jargon that you forget what it sounds like to everyone else? As marketers we live and breathe our industries terminology every single day but so often underestimate what it sounds like to a potential new customer on the street. By creating and sending targeted messages it’s possible to increase the loyalty and lifetime value of a client. Using geo-targeting we can locate a prospect’s city. If, for example, someone in Germany is interested in opening a trading account to buy and sell the DAX, we could serve a messaging layer that will awaken his interest and whenever he or she revisits the website the message is modified based on his or her previous actions. When a user has come back to our site we can serve them relevant messaging based on their last search “Welcome back John! Did you know the price of DAX has jumped 30% since the last time you visited?”.

Marketers have to know the customers most basic information and understand how to perfectly use it, in order for their marketing campaigns to deliver the appropriate messages to their clients. One of the most important points in this context is to know the sources of the available data, and what to do with it. Obviously for an active client existing rich data should be pulled from the CRM system to gain detailed insights and to demonstrate you are listening. The CRM should quickly display the top performing customers in terms of predicted lifetime value. We should also be able to see their age, how many years they have been a customer and their purchase behaviour. Based on this, we can design targeted communication, rather than serving the same message to all.

In any campaign, marketers should track their messages (promotional or triggered messages). The problem is we are often more focused on only reaching our clients’ inboxes and don’t think to track their IPs or domains. It’s important to track these by monitoring all touch points within our campaigns.

The most interesting aspect about Contextual Marketing is the opportunities it offers marketers. Clients are demanding more relevance. The Economist Intelligence Unit Survey stated that Personalisation technologies will have the second highest impact on marketing organisations by 2020. As programmes advance, we need to be open to the possibilities they provide. Marketers should think about the customers’ needs, in order to understand where to focus. Keeping in mind the speed at which people expect a company to respond to their questions and also the ability to quickly switch to a competitor, should drive brokers to spend time working on how they can provide customised automated communication every step of the way.