Digital transformation is now an increasingly default position for C-suite leadership rather than the sole preserve of an enlightened few as it used to be.
Accelerated by a global pandemic that demanded slick, robust infrastructure to withstand disruption and remote working, all while maintaining a seamless customer experience, the enterprise is turning to predictive analytics and artificial intelligence to inform decisions which in turn are creating new ways of working for those steering and shaping these heightened capabilities.
A more human, personal approach
The once black and white narrative around AI as a technology that simply usurps and replaces human effort, offering only basic automation tools and monosyllabic chatbots, has progressed with rapid advances in machine learning and natural language processing, transforming the experiences consumers have with brands by offering far more personalized experiences.
Meanwhile, machine learning means that natural language processing and speech recognition are always improving, evidenced by the conversational AI solutions that can deduce where problems and challenges lie when dealing with a customer. Gradually, almost every facet and role in the business has become digitized - take the role of the marketer, once solely reliant on leaflets and exhibition attendance, now benefitting from apps that, far from taking over their role, are augmenting creativity, reach and potential, leaving them better placed to identify trends across swathes of customer data.
- These are the best cloud storage solutions on the market right now
Pivot, adapt, succeed
Crucially, data analytics are no longer used reactively or constrained by the ability to access only the most recent data in the organization, which meant a limited perspective on the environment.
The rise of predictive analytics has been adopted by many enterprises to help them to identify, understand and react to the vast number of insights buried within the data that they have access to. By creating data pools, we can arm AI to predict customer needs based on real-time analytics, allowing businesses to make real-time changes and cater to customer needs. with forward-thinking analysis, this emerges as a core tool to help better understand the customer and in turn, tweak the proposition accordingly to suit their needs.
Predictive analytics allows you to pre-empt what is going to happen based on the datasets that you have in place, therefore, the more and better-quality data you have, the smarter your assumptions will be.
For enterprise, this offers a unique form of risk mitigation, where you can try to predict potential challenges, peaks and troths and identify trends in the market.
For enterprises operating on a B2C model, predictive analytics enables you to engage in a more meaningful way with your customers. Through the knowledge you have gained from data analytics, you’ll be able to identify personal behavior and trends.
An example of this is if one of your customers frequently shops on a quarterly basis to purchase clothing; you can use data such as the customers purchasing cycles, previous purchase history, and overlay this with other customer data of similar demographics to drive products that would be relevant. Real-time analytics reviewing dwell time on pages can offer personalized discounts that can get them over the line, where they may normally pause to convert into a sale.
By simply understanding the end-customer, you will be able to make more informed decisions that create longer-lasting relationships.
From an operational standpoint, predictive analytics would also allow you to understand what products the best-sellers might be and which might underperform, allowing you to adjust your product suite accordingly. You’ll also be able to make assumptions around stock levels to prevent supply chain issues.
- Check out our take on the best cloud hosting services at the moment
Understanding the customer and building advocacy
Indeed, utilizing the wealth of customer data we now have at our disposal to drill deep into the client account can identify where the attention and resources should be placed now becomes a very accessible focus. Only then are we ready to apply the nuanced and anticipatory interventions, which beyond achieving renewals can lead to greater advocacy, as impressed customers communicate the advantages of the product to others in their network.
The business that can best gather, analyze, and utilize data to garner the most pertinent insights into their audience will be best placed to thrive, which is why success hinges on having the right technology in place, a challenge that can still thwart many organizations.
The type of technology will entirely depend on your sector and specific requirement, but if you take the example of technology within marketing, it’s easy to see the impact that automation and data analytics has had on the industry and its uptake. According to Emailmonday, one-in-two businesses utilize marketing automation, and those that don’t, plan to adopt the technology.
The other benefits for automation in the workplace are clear too, with 81 percent of workers suggesting that automation makes them more productive by saving them at least four working hours per week to conduct their daily tasks, according to a study by Pegasystems.
Technology’s impact on changing business skills
Crucially, these demands mean cutting through established corporate hierarchies and silos to achieve greater data democratization, so that more people across an organization have access to the insight, rather than a chosen few.
The result is creating a more dynamic, opportunistic, and collaborative working environment that is better placed to keep up with the rapid pace of disruption and change. Agile growth is reliant on the continuous monitoring of customer and market conditions, and as the mechanism that creates useful and manageable data based on this information, analytics as a discipline is emerging as a true market disruptor.
History shows us how implementing technology alone inevitably falls short; meaningful change demands a broader cultural shift so that every strand of an organization buys into the innovation and takes responsibility, rather than being just passive recipients of a digital framework imposed upon them.
We see how this plays out to transformational effect when it comes to the use of analytics; how more accessible methods of data analysis, notably via easy-to-read visual representations, enable more people to answer key business questions and make decisions to solve their own issues as they see fit. Imbuing a wider sense of ownership drives data democratization and in turn greater efficiency and productivity benefits for added value to the bottom line.
It explains why establishing a solid foundation of data management is critical - fast retrieval, stringent cleansing and organization is emerging from under the radar to become the lynchpin of effective digital infrastructure. It’s the kind of intervention that signals a shift from the traditional roadblock of complex databases and reliance on specialist staff to a more open and collaborative data culture, which results in systems primed to deliver more effectively in a customer-centric climate.
- These are the best cloud storage solutions for photos and images
Gurpreet Purewal, Associate Vice President of Business Development, iResearch Services