Data is at the heart of any business strategy. Businesses can use customer data to inform user experience and marketing strategies that positively correlate with purchase behaviors. However, many brands simply don’t know how to glean valuable insights from their mass amounts of data. Thus, it’s more critical than ever for brands to understand where their data comes from and how to leverage it to improve online conversions.
What’s the deal with ‘big data?’
Big data refers to the massive, unstructured streams of information that businesses generate on a daily basis. Not only are datasets vast in terms of volume, but they’re also extremely complex and come from a variety of disparate sources across businesses. This, coupled with the sheer velocity at which data is created on a daily basis, makes big data extraordinarily difficult to aggregate and analyze using legacy database and software techniques. Modern technology, however, has increased the processing capacity of various software solutions. Big data analysis is an emerging field providing brands with strategic insights.
Big data analytics deploy a technology-driven strategy to harness powerful data, providing real-time insights into the inner workings of a business. Retailers, in particular, can benefit from extrapolating key details about how to make their e-commerce operations more efficient, as well as how to accurately target and retain consumers.
The rise of E-commerce
The e-commerce sector has exploded in growth in recent years. By 2021, e-retail revenue is projected to jump to $4.88 trillion (in U.S. dollars) in total sales. A confluence of mobile accessibility and swift, secure payment gateways has paved the way for a booming e-retail industry. All those sales are contributing to a simultaneous explosion in consumer data and a new “data economy” for global retailers. The world’s biggest brands are starting to notice how closely the consumer experience correlates with real sales figures. In order to remain competitive, brands have to focus on leveraging big data to improve conversion activities that drive online sales.
Optimizing e-commerce conversions
Data can inform a brand’s digital strategies, leading to increased sales and positive brand sentiment. Companies can optimize their e-commerce conversions using data from a variety of places, including demographic/geographic data, customer experience data, and internal data.
An important data point is the physical location of customers. This insight can be extracted from billing information and the location of website visitors. Demographic data also plays a role in understanding the consumer and how well a product is positioned to capture that target demographic. Household size and other demographics can be determined from social media, customer surveys, and third-party market research groups.
Customer experience (CX) data
Businesses should monitor what their customers say about their brand (and competitors) online. Surveys that pinpoint areas of weakness in cart abandonment, product selection, and customer service all serve as data points that can influence conversion. If you want to read more about customer experience strategies, Apifonica listed 11 tips to improve it.
Critical self-reflection can be a challenge for confident brands who feel poised to capture market share. Auditing data from financial records, inventory management, payroll, and marketing are all core elements that directly impact a brand’s ability to succeed online. Internal company data can point to fluctuating trends in sales, website traffic, ad performance, and more.
3 insights to pull from customer data
Organizing vast data streams into actionable insights can be overwhelming. Large-scale enterprise resource planning systems (ERP) allow brands to integrate critical functional areas of a business into a unified system. Internal and external data can be plugged into tools like these, thereby aggregating a broad spectrum of transactional and behavioral data under one reporting dashboard. This can greatly increase the efficiency of business operations, especially when it comes to data collection and analytics.
Mining ERP data is an effective way to strengthen e-commerce conversions. Let’s take a closer look at a few leading strategies.
1. Conduct a consumer analysis
Being able to effectively target consumers in the digital age requires an in-depth analysis of how and why they make purchase decisions. Globalization and mobile-first consumer browsing mean a competitor is only a click away. Gaining visibility into economic drivers of supply and demand helps retailers plan product marketing months, even years, into the future.
Using business intelligence tools enables brands to use data on past performance, as well as internal and external factors, to predict likely outcomes in consumer behavior. Although this type of predictive modeling is by no means an exact science, the wealth of consumer data at a brand’s disposal can paint a landscape of a specific company’s performance over time. Brands can correlate success metrics down to a specific product, and project future sales success as it aligns with emerging economic and social market trends.
Companies can also leverage product data to encourage greater conversion rates in many different ways. Some businesses in the fashion e-commerce space, for example, use AI to improve product data or to suggest similar items based on what the customer is taking a look at. These tools help retailers cross-sell products and increase conversions and can boost a consumer’s long-term value.
2. Standardize demand forecasting processes
Auditing internal data is a great way to isolate problem areas in the supply chain that impact sales. Omnichannel retailers are using warehouse data to stay on top of inventory management. Retailers that leverage analytical tools to sync their inventory across multiple warehouses are more agile with sell-through on their e-commerce sites. This way, they’re better able to coordinate sales and promotions and maintain customer satisfaction with shipping processes.
3. Increase personalization of product offering
Joris Evers, former Director of Global Communications for Netflix stated, “There are 33 million different versions of Netflix.” Personalizing content has resulted in the streaming giant driving subscriber growth, clocking in at around 130 million users as of summer 2018. The sheer number of subscribers enables Netflix to collect a veritable ocean of data, that AI leverages to help them better their product offering. Not only does Netflix use engagement data to inform the continued existence of their content and green light new series, but they also use it to tailor a user’s dashboard to their specific interests.
Brands certainly don’t have to create their own custom algorithms to make predictions on engagement and projected preferences, but following a similar personalization model can drive conversions. Analyzing past purchases, cart abandonment, and ad clicks help brands make better decisions about price optimization and website design. Personalized “stores” based on previous purchases and product clicks are another great way to leverage personalization to move prospective customers down the funnel.
E-commerce has emerged as a leading driver of sales in the world of omnichannel retailers. In order to maximize ad spend, increase company growth, and build a loyal customer base, brands have to be willing to use the latest tools, concepts, and processes to take a critical look at the hard data.