Four trends to get up to speed with the changed marketing role

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Cat Mules

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AI & analytics martech

In our digital world, we must respond to our customers more directly - and more frequently - than before. Luckily, conversational and AI-led marketing is on the rise. Here’s what to do.

The marketing technology landscape is so diverse that recently counted some 8,000 martech solutions existing in market today. But the digitised world is upon us, and marketers are wise to understand the tools and trends that matter.

We’ve pulled together the main trend areas that’ll get your marketing moving, fast.

TREND 1 – Know Your Customer.

There are a broader range of data points now available – including ID document validation, geo-location and digital footprint analysis, and facial biometrics. You can’t control what customers say about you online, but you can somewhat control what they think and experience about you.

Keep your customer top-of-mind in your marketing campaigns as you explore the many options for data generation.

Caution: privacy is top of mind for customers right now, and repeated faux-pas by Facebook and other social media brands aren’t helping. Once you obtain data from customers, you as a brand are responsible by all means. Research from Sitecore and Econsultancy shows marketers must now work closely with the c-suite to mitigate security breaches and reassure customers.

TREND 2 – Elevate the Human Experience.

The human experience is ever-more important online. Deloitte’s annual report shows how with the lack of human touch online, new voids of experience emerge, to which companies may be pressured to opt for quick fire answers rather than sustainable solutions. This leads to a cycle of customers feeling more isolated, underrepresented and unfulfilled – what  Deloitte terms “experience debt”.

Marketers – often the chief conduit for customer interactions – can help carve relationships out. Lead with purpose, and build your ecosystem around it.

Deloitte themselves say they use human-centered design techniques to train practitioners to practice empathy in all they do. This, they report, leads to greater loyalty, consistency and relevance in the relationship with their customers and their employees.

TREND 3 – The Entire Lifecycle is Worthy.

It’s true that customers are more and more following non-linear journeys – bouncing their attention between tabs and devices, across different brands. Single brand loyalty seems to no longer exist: it’s all about the best experience.

Yet something that will never change: to grow a business, your primary focus must be on your product and service, followed closely by engaging with customers during the lifecycle.

An ‘always-on’ approach to communications should be considered from the customer point-of-view through their journey. Online marketing is impactful when unified with other marketing activities – your use of both offline AND online media should be reviewed.

There are numerous strong solutions available to set up this always-on stance. Salesforce, Intercom and even MailChimp have new capabilities that allow us to set up trigger-based communications. For example, if a customer didn’t click into my app within a time limit, say seven days, you can have an automatic reminder or promo email in place.

And there are a range of potential activities that can be audited, see here.

TREND 4 – Conversations are Marketing Opportunities.

Conversational marketing is a key innovations in the latest Gartner hype cycle, alongside personification and real-time artificial intelligence, which often powers it. Marketers would do well to prioritise their conversational interfaces and messaging in line with this.

As Gartner explains:

Conversational marketing technologies enable interactions between companies and customers that mimic human dialogue and do so at scale. This category is near the Peak of Inflated Expectations phase”.

So, in the face of so many marketing technology options, take care to use the right blend of martech. This will give you an edge over competitors as you access the powerful insights and automation processes that the world’s leading companies are already using to drive value.


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Cat Mules

Umbrellar's Digital Journalist, coming from a background in tech reporting and research. Cat's inspired by the epic potential of tech and helping kiwi innovators share their success stories.

Data, AI, BI & ML

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Artificial Intelligence and Machine Learning are the terms of computer science. Artificial Intelligence : The word Artificial Intelligence comprises of two words “Artificial” and “Intelligence”. Artificial refers to something which is made by human or non natural thing and Intelligence means ability to understand or think. There is a misconception that Artificial Intelligence is a system, but it is not a system. AI is implemented in the system. There can be so many definition of AI, one definition can be “It is the study of how to train the computers so that computers can do things which at present human can do better.” Therefore it is an intelligence where we want to add all the capabilities to machine that human contain. Machine Learning : Machine Learning is the learning in which machine can learn by its own without being explicitly programmed. It is an application of AI that provide system the ability to automatically learn and improve from experience. Here we can generate a program by integrating input and output of that program. One of the simple definition of the Machine Learning is “Machine Learning is said to learn from experience E w.r.t some class of task T and a performance measure P if learners performance at the task in the class as measured by P improves with experiences.”

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