We’ve heard, ad nauseam, that knowledge is power. What we know about our customers, competitors, employees, and community enables us to make meaningful decisions and to influence positive outcomes for ourselves. In the world of business, knowledge begins with data.
For many companies, tripling ROI from personalization efforts brings an opportunity to grow profitably. Business leaders are taking notice of this changing reality and investing accordingly. In fact, the Winterberry Group reported that 78.2% of business leaders plan to increase their spending on data and related services in 2019.
But despite this growing focus on leveraging data and its myriad benefits, are we actually applying the data that we accumulate as effectively as possible? Here are a few efficient ways to put your customer data to work for you.
Smarter customer acquisition
You may be thinking that customer acquisition and lead generation are probably the most important ways in which you apply data currently. Possibly. But if you’re among the scores of marketers who rush into Google Analytics to discover the sources and media that bring you more customers, and pour money into aggressive acquisition campaigns using that data, you’re probably leaving money on the table.
Some of the lesser-used customer data points can be surprisingly useful and can offer stronger ROI than the regularly tried and tested ones.
For example, a simple analysis of the most popular times your users visit your website is a great way to sync your acquisition campaigns to match these times.
Another low-hanging fruit is geotargeting your communications to make them hyper-relevant to customers.
In the dataset above, we see that even though Palo Alto sends less than half the traffic Los Angeles sends, it accounts for 30% more transactions. Steps like creating custom ad copy based on users’ locations, or targeting consumers in high-value geographic segments, are always better than carpet-bombing everyone with the same offers – this will take your ROI higher by more than a few notches.
Lawn mowing company GreenPal moved from targeting the entire Nashville area to segmenting their ads based on profitable zip codes. The custom ads that they created for each segment brought them a more than 200% lift in CTR and a lift of over 30% in on-page conversions.
Better customer experience
Optimizing the customer experience was ranked as the most exciting opportunity for businesses, according to an Econsultancy study:
Web UX, app UI, store layout, and customer service are some key factors that contribute to how a customer feels when interacting with your brand. How you make the customer feel is directly correlated to whether and how much they will spend on your brand. Welcome to the world of customer experience, where each brand touchpoint needs to be designed with the end user in mind.
The first step to optimizing each brand touchpoint comes by understanding your customer journey from your analytics data. Where your customers come from, which pages they spend the most time on, the pages from which they exit your site, the parts of your store with the maximum foot traffic – all these are key data points that offer insights into what aspects of your customer experience need improvement and where you’re doing a good job.
Unfortunately, over half of senior marketers surveyed by Millward Brown admitted that their organizations did not fully understand their customer journeys.
Start by mapping out a cohesive map of the various typical journeys your customers undertake. Then drill down to metrics specific to each touchpoint that you need to optimize to improve the user’s engagement with your brand. Google Analytics’ User Flow and Behavior Flow reports help you better understand such journeys within your website.
Offline, customer experience paragon Starbucks offers a good example. Starbucks found that stores that offer a drive-through option make 70% of their revenues from customers in their cars. In an effort to grow this segment of their customer base, Starbucks dug deep and found that speed of service was the most critical factor affecting UX at drive-through outlets.
That is when they set about building centralized network operations for configuring and managing their menu boards at drive-throughs, digitally instrumenting their drive-through lanes and allowing customers to scan the popular Starbucks app on their phones to pay. These steps helped lift their average ticket size by 20%, and eventually translated into $400 million of new revenue and thousands of delighted customers.
Efficient workforce planning
As we move closer to the end of the decade, we find newer and more complex roles that need to be filled at organizations. HR professionals often lack a complete understanding of the skill sets they’re looking for in potential hires. Roles like AI analyst and marketing automation manager, which did not exist a few years ago, are all the rage.
However, a growing issue is the lack of talent for the most critical roles. Data from Maryville University shows that analytics is the second most difficult skill set to find when hiring new marketing talent.
Competition for talent is so fierce, Gartner found that nearly half of all jobs posted by companies in the S&P 100 in 2018 were for the same 39 roles. When you don’t truly understand what skills you need to hire for and can’t find enough candidates for requisitioned roles, it’s time to change the traditional way of recruiting talent.
Embracing predictive analytics to hire top talent can make the process of finding, converting, and onboarding these employees faster and easier. An agile recruitment approach focuses on the changing demand for talent in the market and starts preparing to search for relevant talent instead of waiting for an internal requisition to open up. Gartner estimates that this method reduces the time taken to fill new-to-company roles by 22%.
Instead of planning for staffing needs by going top-down, a data-driven, bottom-up approach makes sure that hiring projections are more accurate and in line with ground realities in the company. Companies can expect up to 37% lower costs per hire with this strategy.
You can also leverage big data to focus on the right type of talent at lower costs. In the graphic above, data points like job title, location, demand for the role, and average salaries are combined to pinpoint exactly where a human resources team can find talent in highly competitive, emerging fields such as AI, blockchain, and DevOps.
Let data drive you!
Success is often not the result of a new product or idea. Frequently, it is the by-product of using existing resources in a totally new way. Instead of chasing that elusive, innovative, new product, it would serve your business better to look at the mounds of data that are sitting in your servers, explore new patterns in the data, and develop fresh ways to apply these patterns to growing your business.
As Marcel Proust famously said, “Discovery consists not in seeking new lands, but seeing with new eyes.” Go forth and discover with brand new eyes!
For more on creating a customer experience that will grow your business, see “Anatomy Of An Elite Customer Experience Engineer.”