If there is one thing we have learned over the last few years, consumers prefer personalisation, and they yearn for human touch when they interact with brands. If they do not get that, they will move on. Customers expect a certain amount of guided selling and look out for products that interest and appeal to them.
Today, consumer brands such as Amazon, Flipkart, Facebook (now Meta), Shopify, etc., are trying their level best to woo consumers and partners with products and promotions uniquely customised to their preferences and habits. A McKinsey study revealed that personalisation drives performance, and companies that grow faster drive 40 percent more revenue from personalisation than their slower-growing counterparts.
Sign up for your weekly dose of what's up in emerging technology.
The data further shows that when companies personalise communication:
- 76 percent of customers are more likely to purchase.
- 78 percent of consumers are going to refer friends and family.
But, the question is, how can businesses augment customer experience seamlessly to scale their business, offer personalised solutions, and grow faster?
Big data and AI to the rescue
Consumer brands face a sea of challenges to engage and retain their customers. Brands need to navigate challenges across operations, marketing efficiency, inventory management, price optimisation, logistics, etc. The struggle is real.
Big data enables consumer brands to achieve all of these objectives seamlessly. It helps them anticipate consumer preferences and be prepared. Be it Flipkart’s Big Billion Days, Amazon Great Indian Festival, Netflix recommendations, or the most suited credit card options – use of data and AI-enabled technologies help these consumer brands create custom recommendations based on their preferences and affinity, resulting in an exclusive experience for individual consumers and improved customer service. In addition, technology such as these help with forecasting trends and making strategic decisions based on market analysis on the go.
So, what’s stopping consumer brands from leveraging data and AI to power their consumer interactions and boost business efficiency? The answer is, while organisations have large amounts of data at their disposal, it is not easily accessible to all teams. Data democratisation, as the name suggests, is making the large amount of data accessible to relevant teams. If used correctly, it helps scale your business to the next level.
Why is data democratisation important?
Data democratisation essentially means that everybody has access to data. There are no gatekeepers. This free access is also accompanied by arming teams with the knowledge they need to use this data and expedite decision-making to contribute to the company’s growth significantly.
Data-stingy businesses often suffer from the slow decision-making processes made by teams severely restricted in terms of agility. Data democratisation can propel businesses to new heights of performance.
Benefits of data democratisation include:
- Empowers employees with self-service analytics.
- Helps companies in data governance for best use of data.
- Makes teams data literate.
Data democratisation and AI
With the powerful combination of data and AI at their fingertips, teams can gain deeper insights into their customers. Such technologies can also provide recommendations to the next-best-action. Critical decisions such as the right message, right channel, and time can be optimised to boost efficiency as well as delight consumers.
For example, ecommerce brands can identify customers who buy from a specific luxury brand and personalise offers. Banks can determine customers who have not completed the onboarding journey and eliminate roadblocks to help them move towards completion. Music streaming apps can create custom playlists for each listener based on their preferred music and artists.
In the past, these insights were gathered from multiple platforms, most times with the help of technology or data teams running Big Data queries. The time required to run these queries, draw insights, and then apply them was often long. Which meant, brands could not go to the market faster.
However, today’s modern customer engagement platforms offer the benefits of data democratisation and AI within a single dashboard, most times requiring no-code. Forward-looking consumer brands have already invested in these capabilities and are seeing quick results.
Data democratisation in different sectors
BFSI: The banking and financial services sector receives a lot of data from massive amounts of customer interactions and compliance requirements. The industry can leverage data and AI to curate and generate content tailored for each customer. They can ensure the communication is delivered at the right moment and also perform quick and insightful segmentation to predict consumer expectations accurately.
For instance, customer mapping can be done depending on lifestyle needs: housing loans, study loans for children, car loans, or credit cards for family members. This would pave the way for better customer interactions and offerings that are timely and useful. Analytics-driven personalised money management offerings could very well become the order of the day.
Retail: The retail sector is highly dependent on customer engagement. Here data democratisation helps enhance the customer experience as broader access to these insights helps in the overall strategy. Retail brands can easily bridge the gap between their physical stores and digital assets ensuring a unified customer experience. Right algorithms at the right time are showing the way for retail growth, fulfilling customer needs and aspirations. Successful retail enterprises are customer-centric, offering hyper-personalised solutions to their customers with digital technologies at play, customised content, customised product, enhanced quality, customer rewards, and a holistic customer experience.
A final thought Having AI and data democratisation in place can simplify brands’ data-driven decision-making. It can help ensure scale with confidence and speed. According to Accenture, 72 percent of companies successfully scaling AI in their organisation said that a core data foundation was key to their success.
This article is written by a member of the AIM Leaders Council. AIM Leaders Council is an invitation-only forum of senior executives in the Data Science and Analytics industry. To check if you are eligible for a membership, please fill out the form here.