Many brands and businesses talk about being ‘data-driven’ when it comes to sales and marketing, but how many are actually achieving it in a holistic way and at scale?
Being data-driven in sales and marketing involves accessing and analysing data on customers and prospects to inform everything from the products they sell, to the time of day they target prospects and customers, to their retargeting and loyalty program, discounting, and innovation and competitive advantage.
According to Mckinsey, data-driven organisations are 23 times more likely to acquire customers, six times more likely to retain customers, and 19 times more likely to be profitable.
However, often there’s a disconnect between the data available, the quality of the data and the strategy to collate and use it to inform decisions. Data is also often fragmented across a business, sitting in ‘silos’ across marketing, sales, IT and so forth. At the same time, the plethora of martech options claiming to be the ‘holy grail’ customer data management solution makes decision-making complex and confusing, and privacy regulations further complicate the issue.
However, the benefits of data-driven sales and marketing remain clear. Nearly half of the best-performing companies, according to McKinsey, collect and analyse customer data at least weekly, compared with just 16 per cent on average.
Research also shows more than 50 per cent of companies whose revenue growth is in the top 10 per cent are more effective than their industry peers at testing ideas, measuring results, and executing changes to products, services, and ways of working.
Data-driven customer experience in the age of big data
There is no lack of customer data out there. Just through the simple act of visiting a website, many data points can be retained for future targeting and understanding. And while privacy remains a concern, customers have in the past been more than willing to share appropriate data with companies in order to help those companies give them personalised service and a cohesive experience across channels.
Add to this, Australians are turning their backs on brands that disappoint them, with 70 per cent saying they often abandon a brand or switch to a competitor when the online experience is poor, and 42 per cent stating they find it difficult to find the information they need on brand websites.
Studies show 81 per cent of shoppers research a product online before buying it in a physical store.
According to a survey conducted by Aspect Software, 55 per cent of companies have no cross-channel strategy in place, and 90 per cent of customers expect consistent interactions across channels.
Importantly, companies with extremely strong omnichannel customer engagement see a 9.5 per cent year-over-year increase in annual revenue, and strong omnichannel companies see a 7.5 per cent year-over-year decrease in cost per contact.
Informing all of this is data. Companies’ use of data to target customers with personalised offerings, identify pain points and places of churn, provide a consistent experience across channels, as well as targeting and retargeting efforts, loyalty programs and innovation is increasingly becoming the difference to success.
BARC research found those using big data saw an 8 per cent increase in profit and a 10 per cent reduction in cost. Along with this, 52 per cent stated they had a better understanding of their customers as a result.
Leveraging data to achieve the competitive edge
Knowing how to use this data to enhance business activities pays dividends against the competition. According to IBM, 62 per cent of retailers stated information and data analytics gives them a competitive advantage.
Insight-driven businesses are growing at an average of 30 per cent each year and by 2021, they are predicted to take US$1.8 trillion annually from their less-informed industry competitors. By tracking consumer behaviour and gaining an in-depth understanding of them, companies improve customer experience, loyalty, and satisfaction, all of which improve profitability in the long term.
Discounts and special offers
Data-driven discounting can maximise sales, in fact 97 per cent of retailers cite discounting as their top pricing strategy. The right approach to discounting hinges on the product, customers, brand experience, and brand value.
By analysing customer data before and after checkout, as well as retargeting EDM data, brands can quickly and comprehensively ascertain how and when to discount or make special offers, without devaluing the brand or adversely affecting profitability.
As an example, True Vintage’s focus on reviving vintage styles was a hit, especially with a young shopping audience clamouring for what have become among the hottest pieces of apparel in fashion. True Vintage and Shopify Plus found several areas of this retail business that could be supercharged. The most prominent was email marketing, a customer acquisition staple that would give True Vintage a lasting sales foundation to build upon.
True Vintage established itself with a full email structure, a nurture path for its customers from beginning to end: A welcome series, one to aid in abandoned carts, another to thank new customers that’d made their first purchase, and one to survey its growing consumer base.
Before the company implemented its new email acquisition strategies, email marketing accounted for just 3 per cent of True Vintage’s annual revenue – now it is nearly 15 per cent. Thanks to its email communication at large, True Vintage has fostered its own community of loyal shoppers, growing the company’s repeat customer rate by more than 3 per cent year-over-year.
The future of data-driven
Businesses being data-driven has some obvious advantages, and it no longer needs to be difficult to achieve. In fact, innovative and robust e-commerce platforms have a number of data and analytics options which are easy to ‘plug in’ to help businesses deliver exceptional customer experiences at scale.
In fact, good ecommerce platforms have a number of data and analytics options which are easy to ‘plug in’. Find out how Shopify Plus can help you become more data-driven.
