As the competition for qualified talent increases, and as candidates act more like consumers in using numerous touch points for decision making, talent acquisition teams should be asking:
- How do we gather data on interested candidates, and how can we use it?
- How do we offer candidates a compelling relationship with our employer brand at all stages of the job search process and use targeted content to provide value to these candidates?
- How do we build rich candidate profiles that will help us target the right candidates with the right content, and then make data-driven decisions about who to hire?
The good news is that none of these questions or concepts is new. Your marketing teams have been asking, and more importantly, answering these questions about their buyers for the last decade.
How Marketers Use Data for Stronger Relationships
Nearly every (successful) marketing department leverages data on customer interactions to better understand their target audiences and to improve and personalize an experience that makes them want to buy.
In the past five years, marketing has a become a discipline that can be backed scientifically through this capturing of data. Also in the past five years, we’ve seen “data” become the all-too-prevalent buzzword “big data.” And big it is: We’re creating tremendous amounts of it online, with 90% of all data EVER having been created in the past five years (according to IBM).
But while capturing all this data, we’ve only used around 5% to make real analysis that impacts decisions. We are in the infancy of how we use data. So here’s a revelation: Big data doesn’t have to be big—what it has to be is relevant. Most companies can significantly improve their business performance simply by focusing on how operating data can inform day-to-day decision making.
An Amazonian Example
So how does this data capture look, and what insights can you really gain from it? Look no further than the best of the best in customer experience and data intelligence: Amazon.
Every year, Amazon is recognized as one of the most admired brands, and the company’s revenue per user is typically the highest among technology companies. Let’s take a look at how Amazon is able to achieve this.
Consider what Amazon knows about consumers from a raw data perspective. First, Amazon obviously knows what a consumer buys and when they buy it: So when a customer buys running shoes, a hiking backpack and chia seeds in a month, Amazon knows with some certainty that the customer is trying to get into better shape or might be taking an outdoor trip somewhere. With those combination of factors, they thus know some of customer’s likes and dislikes, their hobbies and interests, and ultimately what they like buying at what price. They also know what they’ve looked at and not bought, what they’ve compared and what they might have put in their cart but decided against. It’s incredibly useful data.
On top of buying and searching insights, Amazon also knows financial, location and logistical information about every consumer that visits its site.
So here’s why this isn’t creepy or intrusive:
- Amazon is smart. Through their item-to-item collaborative thinking, Amazon provides consumers with relevant products and services through ads that is integrated in their individual buying process.The suggestions are nearly always relevant, and they don’t get in the way of the user experience if consumers want to ignore them. And in many cases, it enhances it by providing value in relevant recommendations.
- Amazon is trusted. When many consumers research a product, the first place they go is Amazon to read peer reviews. By creating a safe and standard place to review, Amazon has provided an expectation that the star ratings really represent the quality of the products consumers are buying.
- Amazon is easy. With one-click buying, auto-save on all information and an optimal shipping process (including Amazon Prime), they have made purchasing and getting items as simple as possible. It feels convenient every time you buy, and they always strive to make the process easier without losing quality.
But overall, Amazon uses all of this data to consistently create better customer experiences and recommendations for all end users. They provide value and keep shoppers informed, while also notifying users of new and specific items that match their interests. And for Amazon, those better experiences drive conversions that affects their bottom line.
Raise your hand if you want to do the same for candidates: offer real value throughout the candidate’s journey through the data you frame, capture and utilize. To do so, you have to start building a better candidate profile and use it to create better relationships and a better experience for candidates in your CRM.
The Future of the Candidate CRM Record
The standard candidate profile—such as a resume or even a LinkedIn profile—usually offers a “surface” glance of each candidate.
There is a LOT more information waiting to be gathered, and it can be obtained through interactions. If you look at the pipeline for the candidate journey, from the point you attract them to the point you hire them, there are a ton of different tools used and a ton of data present. The problem is that generally, the tools do a lousy job of capturing and correlating that data so that it’s usable.
Following a traditional model with a traditional applicant tracking system, no data from the candidate journey gets tracked until the candidate applies for a job. Think about how much vital information you’re missing that could help you form candidate personas, attract more qualified candidates to your employer brand and improve overall messaging for conversion!
Amazon, data point by data point and interaction by interaction, has created robust data profiles on each of its users. Talent acquisition teams can—and need to—compile candidate data and track their interactions similarly in order to create a dynamic and holistic candidate record that can actually be used to better attract and engage with these candidates and use for decision making and hiring.