A wealth of actionable insights into customer behavior are increasingly the common factor among the most successful brands
The transition to digital has meant that the amount of customer data available to brands has increased exponentially in a short time.
But huge volumes of raw data aren’t helpful to anyone. Instead, brands are turning to data analytics to break down vast amounts of information into bite-size pieces for analysis. This more-manageable data then becomes actionable.
The result? In-depth insights into consumer behavior, the ability to predict future outcomes of campaigns, and more accurate business decision-making.
Successfully leveraging data analytics for competitive advantage is a long-term game. Rather than focussing on short-term conversions, the most successful companies use data analytics to establish a connection with customers that has the ability to stand the test of time.
A customer’s experience with a brand throughout their buying journey is one of the biggest determining factors in their repeat business.
Of customers say that the experience a company provides is as essential to them as a brand’s products or services.
The good news is that assessing key customer service metrics to understand a customer base and then using these insights to improve customer retention, deliver on or exceed expectations and proactively identify opportunities for improvement are all possible with data analytics.
Forrester previously predicted that organizations either need to learn to leverage customer insights and quantify the business impact of customer experience (CX) initiatives or find themselves in a vulnerable position. Another report from Adobe revealed that companies considered “CX leaders” were three times as likely to have exceeded their business goals. While many forecasts are little more than an alternate reality, Forrester, Adobe, and others are spot on about CX. Customer experience is a competitive advantage in every industry, from finance and insurance to healthcare, logistics, and retail.
Of ‘high performing’ organizations worldwide rate themselves as effective users of analytics.
Data analytics are key to ensuring the type of personalized and seamless experience customers expect - at scale, without friction, and with the human element intact.
“With analytics, organizations can develop detailed intelligence about their customer needs. With analytics, organizations can process feedback from multiple sources at scale. With analytics, organizations can tailor offerings specific to customer needs. With analytics, organizations can improve customer satisfaction.”
According to MIT.
Investing in smart CX tools powered by AI and machine learning is booming as brands look to understand customers - through how they shop and what they buy - to improve the customer experience.
Data analytics like those powered by BaaS models allow brands to review multiple sets of data points in real-time that help them understand their customers in context. For example, AI-enabled analytics tools can reveal why some products are more popular with millennials vs. baby boomers, or to identify leaks in the sales funnel.
Data’s role in creating a smooth customer journey might include:
- Tracking why visitors don’t go on to make a purchase
- Identifying gaps in user experience.
- Understanding why people connect with a brand the way they do.
- Identifying similarities between repeat and high-value customers.
- Identifying similarities new visitors have.
- Highlighting what messaging resonates most.
- Pinpointing the best ways to communicate with your customers.
- Highlighting speedbumps in a customer’s journey, including specific pain points and challenges.
Data that is insightful enough to inform you and your team of practical strategies to boost your business is invaluable. Arguably the biggest benefit to your bottom line comes from the ability to personalize a customer’s experience.
According to McKinsey, personalization can increase revenue by 5 to 15% and marketing efficiency by 10 to 30%. Data analytics allows brands to use online behavior insights to create customized landing pages, email campaigns, and offers, and to serve up personalized recommendations to drive more purchases. For instance, checkout abandonment emails or messages highlighting an offer or event specific to the recipient's geographic area are going to feel much more relevant and engaging.
Studies have found that personalized marketing emails result in six times as many transactions as non-personalized messages.
A recent Forbes Magazine article reports that market leaders share a common approach to using data to improve customer experience: they focus on “personalization at scale starting from customer touchpoints back.” Great customer-centric brands recognize that when employees and systems know everything about every customer interaction over time, they can provide better service and support.
Such is the quest for the most optimal customer experience that the relationship between CX and financial gains can hit a point of diminishing returns.
For example, companies often overspend on efforts to attract or delight customers, which typically costs more than improving retention rates or taking advantage of upselling and cross-selling opportunities.
Data analytics helps to find a balance by assisting brands in making sure they allocate their resources where they will have the most significant impact. McKinsey reports that effective use of data analytics can improve customer satisfaction (with an increase of 10 to 20 percent) while unlocking a lower cost to serve (cost savings of 20 to 30 percent in some cases). For these reasons, companies are seeking to step up their customer service offerings to meet the heightened expectations of customers.
Take Amazon, for example. Those constant price changes on their website are not random, nor are they merely an algorithm set to try different prices at different times with no informational underpinning. Instead, those price changes are heavily data-driven and personalized, enticing customers to purchase items they have looked at in the past but not bought, or to consider new items that match their previous purchases on the site. By leveraging big data to analyze customer interest, competitor prices, and inventory, Amazon can price its products in ways that attract and retain customers.
There’s no doubt - knowledge is power. Data analytics provides valuable insight into customers that brands can use to boost a wide range of metrics - including their bottom line.