Marketing and advertising are perpetually changing to keep in tune with the modern hyper-connected customer. The rise of the digital economy means that data-driven customer insights have become the lifeblood of effective marketing campaigns.

In today’s experience-based economy, delivering the right message at the right time is more critical than ever. While the core element of connecting with audiences and converting that interest into action has remained the same for some time, the tools, and technologies now available have revolutionized the way marketers can understand and influence customer behaviour.

In 2013 the then Chairman, President and CEO at IBM Virginia Rometty set an 18-month deadline for marketers to either make full use of Big Data or be left behind. She believed the focus of this data needed to centre on building out individual targeting capabilities, creating a system of engagement, and driving a focus on cultural alignment and authenticity.

With the volume of available customer data increasing exponentially in the last decade, these three areas of focus have become infinitely more challenging for marketers to achieve. The sheer volume and complexity of data now available across the customer journey has pushed marketing experts to the point where they can no longer effectively refine data manually to gain the insights needed to engage with their target audience effectively.

For decision makers armed with little more than legacy spreadsheets and point tools to help them grapple with and sift through a deluge of structured and unstructured data from multiple new sources, social platforms and mobile devices, this challenge is slowing down their time to insights. The phenomenon is in no way limited to marketers, however. While some teams are stuck in spreadsheets, others are cobbling together a mishmash of tools to clean and analyze data. The results are lost time, lacklustre answers and an inability to explore the most important questions: “what happened?”, “why?”, and “what next?” This leaves marketers running blind, causing them to step further away from building longer and stronger customer relationships.

For consumers exposed to a glut of tenuous and often irrelevant messages, information oversaturation and an overload of brand noise is the only key message they see. With the human attention span, as noted in research conducted by Microsoft reduced to just eight seconds – down from 12 seconds in 2000 – there is a huge requirement to deliver what the customer wants, when they want it.

Today, delivering on the highly sought-after personalized customer experience and engagement lies in automating the data-gathering and analytics processes to deliver business breakthroughs; accelerating decision making across the entire customer journey. While marketers need to be able to answer questions at a speed once thought unimaginable, they also need an outcome-driven analytics strategy and the right analytics and data science technologies in place to give everyone the ability to answer these questions.

To stay competitive, surfacing key insights has become mission critical. With the data needed to obtain true customer insights found in many forms, analysing and predicting customer behaviour can sit as one core strategy in the push towards data-driven hyper-personalisation. Many marketers today deliver an inside-out service – attempting to dictate or to convince a customer that what they want to sell is what the customer wants to buy. This is backwards. Marketers need to operate under an outside-in model – assessing what the customer wants by understanding their interactions and how they engage with a business.

Customer interactions hold valuable data that can, when analysed, tell you specifically how to improve the customer experience to maintain confidence and ensuring loyalty. By analysing customer behaviour through social media activity, action on site, clicks, conversions, and sales data, marketers can glimpse trends and quickly offer or direct customers to targeted content. With a vast quantity of data points available to observe and use in delivering a relevant service, there is only one way to stay ahead: analytics and data science automation. Automating how these data points are discovered, brought together, and the process of collecting, cleaning, and drawing insights from them, can accelerate how companies harness this data to get ahead of their competition by driving more lucrative conversions and revenue.

Analytics and data science automation can easily be used to find ground-breaking answers to almost any business question. Although this undertaking does not require a team of experienced data scientists to implement, it’s paramount that everyone in the workforce is able to do it – not just a handful of specialists.

Empowering marketers through a centralised easy-to-use data platform is an essential step in embracing a culture of analytics and refining data to transform it into an asset to inform marketing strategy. Capabilities like self-service drag-and-drop simplicity, code-free automation, along with built-in help and extensive community support all make the data journey easier to navigate. Quickly upskilling marketers with the analytic skills to capitalise on today’s data economy.  

For marketers, this can mean gaining the timely insights needed to drive the relevancy of their offering and treat each customer as an individual.

With just eight seconds to enrapture your customer, anything less than a hyper-relevant offer delivered at the right time will see itself consigned to the void. The marketers who want to succeed 18 months from now are those who can move away from their preconceptions; delivering not what they think their customers want but delivering what they’re actually looking for.

Opinions in this piece belong to the author.