Marketing Bootcamp

Beat the Marketing Competition With Data Analysis

Entrepreneurs mistakenly think, "The more data, the more insight." But diving into a sea of unexamined data can actually harm more than benefit an organization.
Beat the Marketing Competition With Data Analysis
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Many experts think that massive collection and analysis of data is the way to retain customers, but in reality, data’s not enough. And while the field of analytics is continuously growing, only 31 percent of CEOs, according to one study, said they felt confident that their organizations were in the top tier of data analytics users.

Related: 10 Questions to Ask When Collecting Customer Data

What's all this data for? Most companies use it to evaluate performance and optimize programs, but many struggle to determine which data subset is most valuable for understanding consumers and pushing them through the conversion funnel.

Some companies simply decide that large data sets are the most valuable ones. But a mass of unexamined data can harm an organization more than it benefits. What’s most important is collecting the right data and analyzing it effectively.

Surveying the lay of the land

Unless you first understand what data you should focus on, you're going to find it difficult to identify a problem or its solution. If an organization isn’t sure which interactions influence it customers most, it could face endless troubleshooting while looking for the changes that will optimize conversions and retention.

Not knowing which data points to focus on may also prompt many to rely on "vanity" metrics, such as likes and page views. These metrics provide numbers but offer little valuable information. An increase in visits means only that more eyes ran across a page; it says nothing about engagement. That's why startups focusing on vanity metrics risk increasing marketing spend and possibly decreasing ROI.

Companies may also experience analysis paralysis when they collect data and assume that actionable insights will magically follow. This can be a big time and money waster for startups on strict budgets with few resources.

Related: Without Good Analysis, Big Data Is Just a Big Trash Dump

How to collect and conquer

Instead of collecting every piece of data they can, startups should focus on a few key data sets.

Purchase behavior is one of the most important pieces of data to examine. By looking at what customers purchase online, companies can identify what’s truly valuable and meaningful to them. This helps cut through the noise of research and troubleshooting, and it allows companies to focus on what customers have already spent their time and money on.

To further understand customers, companies should also examine which touchpoints customers engaged with or which merchandising messages they received. Companies can then customize experiences for customers and optimize engagement, conversions and retention.

Understanding more about customers’ online lives can help increase ROI and identify opportunities to grow, but it’s not enough. The data collected about customers should be tied to their clickstream behavior to provide a full picture of their on-site activity.

Making consumer behavior your secret weapon

It takes careful analysis of data to identify which behaviors can most impact the business and determine ways to engage and sell to customers. Two of the most important data sets to analyze, according to successful startup founders, are real-time customer behavior and web activity. Once organizations have gathered this data, here are four ways to effectively utilize it:

1. Track absolutely everything.

Organizations should add tracking codes to every link provided -- internally and externally -- to maximize the data available. Consolidate data and analyze performance to connect the dots. Tracking also allows for cross-referencing with third parties to correlate with market standards.

With only 17 percent of companies reporting the ability to fully analyze a customer’s journey from first contact to a purchase, the act of taking this step can provide a boost over competitors. My own team tracked Nike’s sales, for example. We discovered that by partnering with Amazon, as Nike does with other marketplaces, it could boost its sales on the online goliath, fivefold. While Nike executives have their reasons for avoiding this partnership, the information revealed by tracking data is certainly eye-opening.

2. Make experiences speak for themselves.

By understanding how often customers visit a website, what they look at and how often they buy, companies can tailor their outreach and offerings to each user. Craft emails based on past behaviors and purchases to give users the right offer at the right time with product-based triggers.

Starbucks, for example, grew its rewards program 28 percent year-on-year. It now boasts 10.4 million members in the United States, a level enabled by the company’s ability to turn data into better customer experiences and more personalized interactions.

3. Customize interfaces per customer.

Consumers are accustomed to customized experiences. Go one step further than fundamental customizations, by stating the user’s name and customizing websites and services based on actual usage and behavior.

A recent Boxever study found that 60 percent of customers surveyed preferred offers that target their location and behavior. So, to boost performance and sales, promote items related to customers' proven interests -- not a general list or whatever the company wants to promote.

Related Book: Success Secrets of the Online Marketing Superstars by Mitch Meyerson

4. Put social data options to work.

Online advertising platforms, such as Facebook and Google, have audience-targeting functionalities. Facebook’s entire advertising platform is based upon custom audiences, the ability to get extremely targeted by matching your own email file to Facebook users or by selecting specific interests, locations and demographics.

Google AdWords can help companies target new or existing audiences through Customer Match. Upload a CRM file of customers’ email addresses; those that match in Google’s system can be specifically targeted with keyword buys or Gmail ads.

Programmatic display is also a strong way to expand audience reach through look-alike or prospecting models. How those models are built (in other words, how they choose the people the ads are targeted at) is dependent upon the data used to seed them in the first place. Make sure these segments are created using high-quality data that represents the strongest customers for the greatest chance of success.

Related: 4 Ways a ‘Data-Driven’ Approach Anticipates Buyer Behavior

In the end, there’s no doubt that data rules. But companies must take stock of their resources and focus on the data that best serves them. Having the most appropriate data allows for the most meaningful analysis.