Using Data-Driven Intelligence to Stay Ahead in Retail
- by 7wData
What the typical merchant wouldn’t give to be able to read a customer’s mind. The next wave of retail technology will focus on offering merchants more insight into the customer’s considerations and preferences while shopping. Data-driven intelligence will ultimately enable retailers to cater to customer needs in a more individualized and sophisticated manner, without expending excessive effort, expense, and resources.
Simply put, data-driven technologies leverage specific parameters provided in the path to purchase, and apply or create rules based on these details. For instance, if the technology detects a consumer paying in-store in Russia with a Chinese mobile wallet, the business could automatically send the consumer promotions for the local Chinese store. Or, if the brand is based in Russia with an online presence, the company can send online offers timed for local Chinese holidays, such as Single’s Day.
There are just a few of the many ways that retailers can leverage their data and optimize customer experiences without compromising data security or operational efficiency. Read on to learn how some retailers are analyzing consumer data to better understand and meet customer needs.
Understanding Various Paths to Purchase
The objectives behind most data-driven technologies are two-fold: to answer customer needs and meet customer preferences. These technologies are used to discover what customers need by identifying where customers are wavering or abandoning the path to purchase, and, conversely, those elements which most encourage customer conversions.
Identifying and Solving Problems
Better data resources can help merchants identify the specific point in the customer journey where customers abandon the purchase, and cross-reference this information with other parameters to deduce why customers are not converting.
Location-Based Optimization
One parameter that greatly impacts the customer service that retailers can offer is the geo-location or IP address of the consumer. By simply knowing where a consumer is based, the retailer can offer targeted promotions, share relevant information about its brand in that locality, and provide a consumer experience tailored for the cultural conventions of that location.
Maximizing Payments Rules
Many consumers will abandon their checkout at the payment stage. Sometimes this is because the payment methods they prefer to use are not available to them on the merchant’s website. Other times, back-end inefficiency prevents consumers from actively checking out.
Intelligent Transaction Routing
Better data can also save merchants money when it comes to processing customer payments. Merchants pay fees when their customers pay by credit card or alternative payment methods, but with better data about the financial institutions with which they are partnered, they can create more intelligent rules to decrease transaction costs.
Globalization and Personalization
Merchants are starting to expand their customer bases to include international consumers. As they reach new regions, they are starting to learn just how cultural consumerism is. Without insight into the international customer journey, retailers are at a loss when it comes to the products different nationalities want to buy abroad and the payment methods international consumers prefer to use.
Enabling Omnichannel Retail
Many of today’s major retailers strive to offer customers an omnichannel experience and maintain both online and brick and mortar stores. With more transparency into their consumer data, merchants can better understand customer interactions at each channel and optimize performance for each platform accordingly.
Empowering Marketing Initiatives
Access to data has utility beyond the in-store or online shopping experience. Retailers can leverage data to bolster retargeting and marketing efforts across channels, to encourage future shopping experiences and attract new customers.
Detecting Fraud and Securing Data
While merchants often associate the benefits of accessing customer data with the risk of increased fraud and data breaches, oftentimes data can be leveraged to provide a more secure shopping experience. Today, retailers can integrate data tools that learn customer behavior, detect anomalous behavior, and flag it as potentially fraudulent.
Challenges of Big Data
Although data-driven technologies have many benefits for retailers, using and storing data is not without its risks and challenges. To store customer data, merchants are required to comply with a number of regulations and security protocols, many of which are time-consuming and vary by country. Keeping track of all the requirements and maintaining compliance for a company can become a full time job.
Possibilities of Big Data
Big Data is changing the retail experience – even in its early stages. For years, merchants have been leveraging saved customer data to enable one click checkout. In the future, we can expect even more data-driven technologies and better capabilities:
- Automating processes – Data will enable merchants to automate business processes that involve a lot of time and resources, by creating rules.
- Decreasing fees & declines – Merchants can cut costs by analyzing payment information and routing transactions to local payment providers globally.
- Increasing revenues – Not only will data save merchants money; it will help them increase profitability by addressing customer needs and preferences.
- Efficiency through knowledge – Better visibility leads to better operations by helping retailers see inefficiencies and make improvements through analysis.
[Social9_Share class=”s9-widget-wrapper”]
Upcoming Events
Strategies for simplifying complex Salesforce data migrations – Free Webinar
27 March 2024
5 PM CET – 6 PM CET
Read MoreCategories
You Might Be Interested In
4 ways to optimise your existing big data investments
8 Jul, 2015For big data, the day after tomorrow is here. Gone are the days of CIOs and CMOs talking about …
Business analytics services spending to surpass US$100 billion by 2019
4 Dec, 2015Worldwide business analytics spending is expected to reach US$58.6 billion in 2015 and US$101.9 billion in 2019 – a compound …
A Computer Just Solved This 100-Year-Old Biology Problem
7 Jun, 2015Big data—and big processing power—is a big deal for science. By crunching massive amounts of data billions of times …
Recent Jobs
Do You Want to Share Your Story?
Bring your insights on Data, Visualization, Innovation or Business Agility to our community. Let them learn from your experience.