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How to solve common marketing challenges with intelligence

10 October 2019Samuel Miller

What if we told you that by adding intelligence into your MarTech stack you could drive efficiency and effectiveness. It sounds like a win, right?

In today’s digital marketplace customer experience is the key differentiator and marketers have become Experience Makers. As such, they are constantly bombarded with more and more competing demands for their effort and spend. So delivering better results from your current technology stack or getting more for a minimal investment is always a welcome outcome. Enter artificial intelligence, stage right.

What do we mean by intelligence? Making your customer experience smarter to improve results; whether that is greater brand awareness, improved conversion rates or any another desired outcome that is driving your marketing strategy.

Artificial intelligence and machine learning features and solutions are being added into MarTech stacks at an unprecedented rate. In fact, it’s never been easier to move the heavy lifting to smart processes. This could be the application of advanced analytics to smart tag assets, making your content more usable and discoverable; having a better understanding of who your customers are to target them more effectively; or automating processes with AI/ML, making decisions for experience delivery that save effort and cost.

We’re constantly advising clients on developing a smarter stack and have come up against some common challenges that AI is solving. Here are 4 great examples where the addition of intelligent features to the technology stack provides a better solution.

1. We can’t build a coherent picture of our customers that we can act on in real-time

This is all about context. Context covers what we know about the situation and moment we’re marketing in. It helps us to understand the customer and their decision making process. And it helps us to reconcile all of this to deliver a relevant experience based on what we know.

The hard part is piecing it all together to gain a clear understanding of your customer, in a single place and a single moment, that is easy to analyse and act upon. It involves integrating data from multiple sources, which can be difficult and time consuming, even on integrated marketing clouds.

This is known as the single customer view (SCV) and achieving this holy grail is growing in importance. With this in mind, the rise of the Customer Data Platform makes a lot of sense.


Unlike traditional CRM solutions, CDPs provide built-in machine-learning automation that can cleanse internal and external data, connect a single customer across devices, cookies, and ad networks, and enable real-time campaign execution across touchpoints and channels.



CDPs allow data to be intelligently pulled into a single repository, rather than spread across point solutions, so that it can be acted on, in a coherent way, across channels, in real-time. It helps that the best CDPs are easy to use and can be implemented quickly, compared to custom solutions that link existing data held in other marketing solutions. So you’ll see your ROI much sooner.

And once you have your CDP up and running, ingesting data and creating accurate customer profiles, you can start to run advanced analytics that will bring you even more value. For instance, you’ll be able to predict Customer Lifetime Value (CLV) and identify those customers most likely to churn. So while you’re driving new customer acquisition at one end of the funnel, you can target relevant messaging to prevent losing customers at the other end.

2. We’re still not feeling the value of personalisation

Personalisation is probably still at the forefront of your marketing agenda. However, a recent McKinsey survey of senior marketing leaders found that only 15% of CMOs believe their company is on the right track with personalisation. For clarification, because there are many interpretations, we take personalisation here to mean the capability to tailor messaging based on both one-to-many and one-to-one. To effectively deliver this type of experience, it takes the context we have detailed above and adds in the challenge of having relevant content, in the right form, ready to be delivered.

So you need to make your content smart. Adding in some smarts to the asset management and content creation process can massively reduce the effort needed to support your personalisation efforts.

Tagging images so they can easily be pulled into marketing activities is often still a manual task that takes resources away from more value-driving activities. You can make your stack smarter by using built-in smart tagging features, such as Adobe enhanced smart tags. This kind of solution will automatically assign new images with relevant tags. And if it’s not a feature in your stack, third party options are available. While there is an overhead associated with setting it up (and potentially updating it), in our experience, it will soon start to prove its value.

It’s not just images that can be impacted by a smart content drive; what you say, when and how you say it is massively important and smart options exist to optimise this too. Take Persado, for instance. It machine-generates copy based on emotional resonance for specific segments and analyses which key phrases or words succeed in delivering the desired action. This can lead to impressive results. Dell recently used Persado in an email campaign and saw a 50% average increase in CTR, and a 46% average increase in conversion (reported by Econsultancy in a round-up of machine-learning based email marketing).

Once you have identified your target audience, analysed the context of the personalisation and created relevant content, you actually have to deliver the experience and measure its impact.

Running tests and choosing the best variants for personalisation can be a time-consuming process but luckily a smarter marketing technology stack has a solution. Instead of manual monitoring, you can employ machine-learning based delivery and activation. This measures competing versions and automatically targets the best performing variant.

Using these smart features together provides a powerful personalisation capability, and the associated results, with less effort.

3. We’re struggling to deliver a coherent experience across channels

With customer expectations for a coherent and seamless experience across channels, this has to be a priority. But it means that your marketing capabilities, including personalisation, need to speak to each other, rather than act in silos, and deliver across channels.

One possible solution is a Customer Engagement Platform. It adds intelligence to your experience delivery by pulling data from a number of data sources, including your CDP and other point solutions, such as web analytics or a CMS. This cross-channel data can be acted on in real-time, with intelligent recommendation engines, to activate coherent messaging across multiple channels. These engines help marketers get much closer to delivering true one-to-one personalisation throughout an entire customer journey, with built-in AI/ML learning that tracks what people respond to and starts recommending what should be served up to deliver the desired result. Customer Engagement Platforms work in unison with experience cloud solutions and CDPs to create a powerful and effective digital experience platform.

4. My team are too busy to deliver actionable insights from web analytics solutions

Analytics is the key to having the necessary signals to guide change and optimisation. However, many organisations have the data coming in but not the insights coming out.

This is a time and effort challenge rather than a data availability problem. Luckily, there are a number of smart features that have been added to web analytics solutions that can get to key actionable insights with minimal time investment.

Take Intelligent Alerts in Adobe Analytics, which alert analysts if there have been significant changes to behaviour on websites and identify what is behind these changes. Very useful when you are seeing a drop in conversions after rolling out a new feature and you can’t tell what is causing this drop or whether something is broken. It’s a shortcut to getting to the cause of the problem quickly. It is worth exploring what smart features are available on your analytics platform.

Four common problems with several smart solutions. Technology is getting smarter and easier to use and this trend for baking AI/ML into marketing tools is set to continue and improve. And in turn, intelligence help humans to get smarter because it allows marketers to focus more on the strategic elements, rather than the repetitive and low-value tasks.

If you want to have a conversation about making your customer experience capabilities smarter, get in touch.

Photo by Jukan Tateisi on Unsplash

Author: Samuel Miller
Published: 10 October 2019
analyticscustomer experiencemarketingmarketing technologypersonalisation

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