Data and Analytics capabilities are more effective than ever. And yet many B2C companies are failing to leverage the power of the tools at their disposal. In the fashion sector, during the Covid-19 pandemic, retailers saw their sales drop by 20% between 2019 -2020. With the continued expansion of the online market and the influence of social media and other channels on in-store purchases, harnessing the power of data is key to re-engaging with customers, offering superior user experience and increasing sales and efficiency. Data can be successfully integrated to maximise sales potential in both online and physical points of sale. Those companies that successfully navigate data privacy laws and customer preferences to extract vital information to enhance their sales and marketing activity by integrating data and analytics into their overall strategy look set to reap the rewards.

Key Benefits of Data

Personalised Customer Experience (CX)

Personalisation of the buyer’s journey can improve the user experience and prioritise customer care, thereby increasing client loyalty. As McKinsey & Company report, fashion companies who have leveraged the power of data to personalise e-commerce experience have achieved an online sales growth of between 30 and 50 percent. Those businesses which have put in place an architecture of personalised interaction with consumers via multiple channels have seen a 20 percent increase in their revenue. The powerful AI technology available today can even help to predict size and fit and therefore minimise returns of online purchases, which not only leads to higher customer satisfaction, but also helps to reduce costs.

The Value of Analytics

Analytics can provide a wealth of information that can enable B2C businesses to gain the edge over their competitors. Basket analyses, loyalty cards, and data capture can provide valuable information on consumer profiles and behaviours, as well as enable a company to make decisions supported by data in both their overall operations and short and long-term marketing strategies. The same McKinsey report found that 700 companies worldwide who invested in analytics to predict future market trends and conditions, target customers more successfully and optimise supply chain procedures achieved operating-profit increases of around 6%. Those who integrated a wide range of data into their analytics strategy saw the best results.

Increased Operational Efficiencies

The rewards that come from investing in a robust data and analytics strategy are not just limited to sales and marketing benefits, but to an improvement in overall efficiency across company operations as a whole. B2C companies who successfully integrate data into their planning, production and
supply-chain operations can reap the benefits of reduced operating costs and higher profit margins. Businesses can easily identify their power products, evaluate channel efficiencies and the success of any promotions to optimise pricing policies. The successful deployment of a data analytics strategy can result in astronomical savings. As Stephen Ezell, the Vice President of Global Innovation Policy at the Information Technology & Innovation Foundation, reported: “One US automaker estimates that its implementation of IIoT combined with big data analytics has saved it over $2 billion in operational costs over the past five years—a return on investment of over 400 per cent of the approximately $350 million investment that they made.” 

React to Market Trends

The use of predictive analytics tools enables companies to identify market trends and customer behaviour patterns, as well as competitor activity. This not only means that businesses can forecast demand peaks and plan their operations accordingly, they can also use this data to extract valuable information to guide their marketing strategy and tweak it accordingly. Those companies that stay one step ahead of customer trends and behaviour patterns will see a higher ROI when it comes to their
marketing activity. The ability to react swiftly to changing trends will also result in increased customer retention as existing customers will be less likely to search elsewhere when their brand of choice can supply their desired item.

Reach Out to Customers with Solutions that Deliver Value

By combining features such as loyalty cards and analysing data collected from online purchases and behaviours, companies can proactively offer their customers solutions. Perhaps the most well-known company that actively reaches out to customers in this way is Amazon, with its personalised product recommendations based on its item-based collaborative filtering algorithm. It also makes use of data collected from a user’s general browsing history to suggest products that align with their interests. Other examples include online gift stores which offer reminders and suggestions for special dates or loved ones’ birthdays.

Sustainability

Sustainability is one of the top concerns among today’s conscious consumers, and using analytics to achieve this doesn’t just positively impact a brand’s profile and the environment, it also assists in reducing operating costs and avoiding resource shortages and sharp price fluctuations. Businesses can promote their sustainable practices with full data-backed transparency, while also anticipating future market changes and therefore optimising resource management and predicting emerging risks to avoid operating practices that might result in negative environmental or social impacts that can quickly make headline news. Implementing analysis of sustainability data into a company’s overall procedures and constantly refining this can help lay the foundations to build a resilient and solid business infrastructure.

How to Achieve Consumer Data Sharing

While there are more available and powerful AI analytics tools available than ever before, conversely customers are becoming warier than ever about freely sharing the data that marketers need to create a personalised user experience. According to the Boston Consulting Group, two-thirds of customers want ads that are personalised to their interests, yet nearly half of consumers are uncomfortable with sharing their data to facilitate personalised ads. Businesses, therefore, need to take a proactive approach to data collection and address consumer concerns with transparency in order to build trust and make customers feel at ease with providing this information. The Boston Consulting Group partnered with Google and found that the three most important issues to consumers are:

1) What data is being collected?
2) What will it be used for?
3) How is the data collected?

They also found that the data consumers were most comfortable sharing varied according to the consumer demographic. For example, young urban professionals were 113% more likely to share their social media activity, while wealthy and retired consumers were 53% less willing to share their income. Most consumer groups were also more willing to share their data in return for incentives, to varying degrees. However, nearly all consumers were concerned about the privacy of the data they provided and whether companies were protecting it.
Therefore, businesses that proactively build a relationship of trust and transparency when it comes to data collection, as well as demonstrate the consumer value in the provision of such data through improved personalised experienced and smoothing the buyer’s journey, can expect to achieve a much more successful outcome in collecting the data that will add value to the consumer experience and subsequently drive a company’s growth and brand image in the long term.