The Difference Between Collecting Data and Acting On It,
Big data is one of the most frequently discussed concepts in marketing today. While most marketers collect data, not all marketers consistently take action to improve their businesses based on data insights.
In a study on UK businesses in the digital economy, it was discovered that only 18% of businesses relied on data and analysis when making revenue-generating decisions – despite the widely publicized benefits of a data-driven approach to sales.
Before the Information Age, data collection was a slow and arduous process. Fortunately, now we have access to software that automates data collection.
With Kissmetrics Analyze, you can quickly generate in-depth reports and see how people are interacting with your website. With no history limits, your data reserve will only continue to grow as time goes on.
For PPC advertisers, Facebook offers an incredible array of data insights. Every time you run an ad campaign, you can see your ad’s cost per click, cost per purchase, click through rate and more.
This not only allows you to make inferences about your campaigns, but also about the audiences you’re targeting.
If you have a massive collection of customer data but aren’t using it in any meaningful way, this represents an untapped opportunity for business growth. If this sounds like you, don’t feel bad, there are steps you can take now to start getting a return on your data collection immediately.
List segmentation is a simple but effective tactic for utilizing data in email marketing. By recording consumer behavior, demographic and psychographic information, you can come to conclusions about the types of content people would like to receive via email.
In this regard, email becomes a more personalized communication channel.
In a survey by Econsultancy, 74% of marketers stated that personalized email marketing increases customer engagement. Likewise, in a study by Campaign Monitor, marketers noted a 760% increase in revenue from segmented campaigns.
With Kissmetrics Campaigns, you can utilize behavioral analytics data from Analyze and send automated emails to people who have flipped specific triggers on your website.
For instance, you wouldn’t want to send the same email to a hot lead and a new email list subscriber. If a person has visited a product page multiple times, has viewed pricing information and has shown other indicators that they’re ready to purchase – it would be appropriate to send them an overt sales email promoting the particular product.
For new email list subscribers, it’s far more effective to send them a sequence of emails where you deliver value and offer actionable advice before delivering a sales pitch.
With a data-driven approach to email marketing, you can use automated emails to push people through your sales funnel – whichever stage they’re currently at.
32% of executives say that retaining existing customers is a priority. It’s surprising that this figure isn’t higher, because acquiring new customers can cost 5-25 times as much as retaining existing customers.
When executing a retention strategy, the more consumer data you have to act on, the better.
By analyzing a person’s purchasing history, you can gain insights into what other products they would be interested in.
If you have three primary products in an ecommerce store, and a person has purchased two out of the three, there’s a very high chance that they’d be receptive to marketing for the third product.
In addition to personalized email marketing, you can upload this ultra-specific list of buyers to Facebook and create a custom audience.
Next, run a Facebook ad to this audience of previous customers and promote your product. Because you’re a brand they already know and trust, the click through rate and cost per purchase will be much lower than when you advertise to cold audiences.
If you run a SaaS business, you might want to set up an event trigger whereby existing customers receive an appreciative automated email exactly one year after signing up to celebrate their anniversary.
Your data will tell you which of your customers have the highest likelihood of becoming brand advocates. Keep this in mind when promoting loyalty programs.
A data-driven approach to retention marketing isn’t about extracting as much money as humanly possible from your existing customers.
Instead, it’s all about offering a great customer experience with personalized content and offers. This mindset is much more beneficial for long-term brand building and it’s also highly lucrative.
In a survey of over 300 marketers, 90% said they are using visual content in at least one-half of their posts.
Data visualizations, like infographics, are useful for communicating interesting information in a visual context.
Although the terms data visualization and infographic are often used synonymously, they’re not the same thing. Data visualization is all about showing data in creative ways, while infographics follow an explanatory narrative.
Data visualizations are often key elements within infographics (but can be standalone too) and are created using computer algorithms. In order to generate a beautiful data visualization, you typically need a large reserve of data to draw from.
Showcasing customer data as a colorful visual display is a great content marketing tactic. You can simultaneously make your business more transparent while educating your audience about the importance of churn rate, customer retention, customer lifetime value and other metrics.
Data visualizations are useful for internal purposes too. Oftentimes, trend analysis becomes much easier when you have visual aids as well as statistics to draw conclusions from.
If your organization is launching an HR initiative to improve workforce diversity, recording and visualizing quarterly data would help you to assess the efficacy of your initiative. These kinds of visualizations could be used in presentations given to senior leaders, shareholders and prospective customers.
Predictive analysis refers to the practice of analyzing historical data in order to identify the likelihood of certain future outcomes. With a large sea of customer data at your disposal, predictive analysis can be extremely beneficial in terms of product development.
For anyone that has run an ecommerce store, it can seem baffling which products are successful and which fail – irrespective of prior market research. For successful stores, a couple of products typically bring in the vast majority of the store’s profits, while other products remain largely unsold.
For this reason, introducing a new product to the market can often feel like a huge gamble.
Netflix is one brand that has mastered the art of predictive analysis. Based on a large amount of data, Netflix identified attributes of successful movies and television shows.
The insights they gather has allowed Netflix to create House of Cards, which has been a huge commercial success. Series star, Kevin Spacey, and producer, David Fincher, were picked specifically because Netflix viewers had enjoyed their previous work (as verified by data).
Predictive analysis cannot completely ensure your success when developing a new product, but it will definitely help to improve your chances.
Predictive analysis can also be used to reduce churn rate, as American Express demonstrated. By using analytics, they’ve gathered insights that help them avoid the “gamer” customers and attract more loyal, high-quality customers.
When you have a list of accounts which have a high likelihood of closing, you can launch a specific email marketing campaign for re-engagement. This may include offering special rewards, showing appreciation for customer loyalty and delivering valuable, personalized content.
Even if your ability to perform predictive analysis isn’t as sophisticated as American Express, there are certain factors which strongly correlate to churn rate – such as a person not logging into their account for a certain duration of time.
With Kissmetrics Campaigns, you can setup a time specific event which triggers an automated re-engagement email. Sports betting companies are notorious for this, sending customers free bet offers if they haven’t engaged in a while.
By looking at purchasing patterns of previous customers, you can make sales forecasts for the future.
If your main source of revenue is from your mailing list, knowing the cost of acquiring an email subscriber, your average order value and customer lifetime value is crucial. With this information, you’ll know exactly how much money you can pump into acquiring leads so that you can scale your mailing list profitably.
If you don’t know the key metrics for your business, it’s very difficult to budget your marketing activities properly.
When using predictive analysis for sales forecasting, it’s helpful to provide a pessimistic forecast as well as a neutral forecast based on current data. Metrics won’t stay completely consistent as you scale, so it’s important to have some extra money available if your sales forecast doesn’t work out as well as you intended.
Can you think of any other data-driven ways to improve your business? Please let me know in the comments below.
About the Author: Aaron Agius, CEO of worldwide digital agency Louder Online is, according to Forbes, among the world’s leading digital marketers. Working with clients such as Salesforce, Coca-Cola, IBM, Intel, and scores of stellar brands, Aaron is a Growth Marketer – a fusion between search, content, social, and PR. Find him on Twitter, LinkedIn, or on the Louder Online blog.
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