Data Analysis

Want to Be More Like Amazon? Start By Making Your Startup More Data-Driven.

Most companies understand the importance of customer data, but lack the analysis expertise to match their ecommerce competitors' level.
Want to Be More Like Amazon? Start By Making Your Startup More Data-Driven.
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Guest Writer
CEO, Jumpshot
5 min read
Opinions expressed by Entrepreneur contributors are their own.

Amazon has cultivated a well-deserved reputation for owning the online shopping market; but contenders like Walmart are looking to gain competitive ground. The supermarket chain, for example, moved earlier this year to offer two-day shipping for no additional charge with any online order. Sound familiar?

Related: 5 Ways Startups Can Leverage Big Data for a Competitive Advantage

But, even with this change and the company’s recent acquisitions of specialists like Jet.com, Shoebuy, Bonobos, ModCloth, Adchemy and OneOps, Walmart still has its work cut out.

After all, super-powered companies such as Amazon don’t emerge by chance. Over time, Amazon has mastered the art of conversion by developing strategies from the data it's collected on customer behavior. Which brings us back to Walmart: Without a stronger sense of how to diagnose its own market and pin down its customer intent online, even a company this powerful stands no chance of claiming a piece of Amazon’s turf.

All that, in turn, brings us to your company: If a giant like Walmart is struggling, much smaller startups might consider it a hopeless task to even make a dent in the ecommerce space. But there are methods startups can employ to cover lost ground using data. According to a survey by Interana, 88 percent of companies polled reported that while they understood the value of data, most admitted they struggle to implement accurate, agile analytics solutions.

Closing the consumer data gap

One way to solve this disconnect is to employ second-party data with publisher partners. OwnerIQ reports that 96 percent of companies incorporating second-party data into their marketing strategies acknowledge it as valuable to their strategic success. When campaigns are running, you too should work with publishers that effectively segment audiences and make in-flight adjustments to ensure campaign dollars are spent effectively.

Startups can also exchange first-party data through a data onboarder such as LiveRamp, which has about 200 direct relationships with clients. Once the marketing team has developed a holistic view of first-, second- and third-party data, you can put all those types of data to work with platforms that help target, personalize and measure against all marketing efforts.

Related: 7 Startups That Are Owning the Data Game

Then, once entrepreneurs have built up their startups’ data sets, they'll hopefully see how vital it is to use that data to its full effect. Data is nothing if startups aren’t drawing insights from it via analysis. Want to know more? Here are four ways startups can give themselves a boost up to their ecommerce competition’s level, through an effective use of data.

1. Make data sets manageable.

Data analysis is time-consuming, but it's not impossible. In fact, a CMO Council survey found that 42 percent of marketers surveyed were seeking to analyze more connected marketing campaigns. A separate 30 percent of professionals who deal with data reported to Square Root that they were regularly interacting with an overload of data sources.

Tip: Consolidate your own data sources into one manageable environment instead of forcing your marketing team to hop from platform to platform. Pull all in-house, second-party and third-party data into one data warehouse before starting the analytics process.

2. Keep analysis goal-centric.

As with any efficient marketing strategy, data-analytics strategies should relate to relevant company goals and product development. Focus your resources on collecting data in areas that have the biggest influence on your company goals, and analyze the data accordingly. Data programs that work well and are efficient tend to focus on examining customer-behavior data and creating product iterations based on what that data reveals.

Home security startup Vivint used customer usage data from its doorbell camera to determine that its product was used most by families with children on weekday afternoons. This insight led to the development of a new product entirely -- a two-way video chat product called Vivint Ping that allows working parents to stay in touch with their children who have arrived home from school.

3. Measure data that matters.

KPIs are no good if they aren’t measuring data points that are useful to your company. Ensure that the KPIs your marketing team tracks are optimized for the company’s overall goals and its products or services. These KPIs can range from lifetime value to margin loss, but no matter what they are, they should be useful markers for the company.

For entrepreneurs struggling to determine which KPIs are most relevant for their companies, consider some options: Customer-acquisition cost (the cost spent on marketing efforts to gain a new customer), lifetime value (a customer’s overall value to a company) and profit margin (how much is made from a sale of a product above its production cost) are good metrics to watch.

4. Examine data companywide.

Don’t keep data siloed in one department alone, because that just makes each department less likely to connect the dots. An ecommerce department, for example, might struggle to understand which campaign or platform first attracted a given customer, and marketing won’t be able to optimize a campaign without knowing where people left the conversion funnel.

Related: 5 Misconceptions Small-Business Owners Have About Big Data

Cross-department collaboration also ensures that offers can be tailored to specific customer groups throughout the funnel. The Aberdeen Group found that not only does collaboration make decision-making 46 percent faster, but customers are treated to response times 42 percent better as well.

Developing a successful data strategy can seem daunting, especially when companies as big as Walmart are struggling to keep up with Amazon’s prowess. But keeping these four characteristics of data strategy in mind could help push your startup to the front of its industry segment's ecommerce pack.

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