Don't Waste Your Budget on a Social Influencer -- Use Data Instead A data-driven strategy teaches a business about its customers' motivations and interests, helping it build an engaged community.
By Deren Baker Edited by Dan Bova
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Even non-fans of the Kardashian clan probably heard about Scott Disick's recent Instagram fail: The reality star was posting a sponsored Instagram post for a weight loss supplement, and accidentally copied and pasted his instructions for posting within the comment box.
Related: Why You Don't Need Kylie Jenner As Your Next Brand Influencer
So went what is only the latest example of digital marketers' repeated frustrations with social influencers.
Because of incidents like this, high-profile entrepreneurs like Calvin Klein have expressed reservations regarding social influencers' efficacy. And that's happening even as the leading names among this elite crew are charging as much as $20,000 per post. So, are they worth it?
Most marketing campaigns rely on quantitative data to measure ROI, but content posted by social influencers cannot be tracked through traditional metrics. After the expiration date on trackers like cookies has passed, it's impossible to trace the full sales funnel.
Marketers also have no direct control over the content, which can create problems with scheduling, and there is no guarantee that a social influencer's post will have an immediate impact.
Related: 5 Signs You Need to Start Tracking Marketing ROI
With no base value system -- considering that prices vary from influencer to influencer -- cost is another issue. How much is a new follower or a Twitter mention worth? One influencer might have more followers than another, but does the brand message resonate with that influencer? Throw in other concerns, regarding price transparency and content ownership, and digital marketers with limited budgets are left scratching their heads.
Instead of wasting time trying to get the social influencer model to work for their brands, perhaps they should turn to data instead.
How a data-driven approach reaps big rewards
Seventy-seven percent of marketers in one survey said they were confident that the data-driven approach is the right one, and 53 percent said they believed it makes their endeavors more customer-centric. From ad network reporting to social media analytics, every marketer has access to a wealth of data that offers a range of possibilities.
Paying a social influencer instead is risky, and requires marketers to strategize correctly from the beginning. In contrast, a data-driven strategy allows for multiple iterations to find the perfect message. While those variations consume resources, they also reveal what resonates best with an audience -- helping marketers optimize their message, zone in on the platform and craft whatever format works best for the brand, ultimately creating a more effective strategy.
Social influencers might bring customers to the website, but they cannot push people through the funnel or let them explain why they left before making purchases. Are there too many steps in the registration process? Is nonessential information requested? Data can answer these questions and establish long-term relationships along the way.
An effective data strategy, therefore, goes beyond one-way communication -- it teaches a business about its customers' motivations and interests, helping it build an engaged community. The data-driven approach might take more legwork, but the results can be very powerful.
Putting data back into growth marketing
So how can marketers capitalize on the potential of data to generate awareness and drive business? Here are five simple steps:
Track everything. Add tracking codes to every link provided internally and externally to maximize available data. Consolidate it, and analyze performance to connect the dots. Then, cross-reference with third parties to make sure the results correlate with market standards. Keep in mind that a 5-to-10 percent difference between ad network and advertiser analytics is commonly accepted.
Use data to offer personalization. Knowing how often customers visit a website, what they look at and how often they buy allows marketers to tailor their outreach and offerings at the user level. A social influencer only sends one message, but a well-crafted data approach allows marketers to personalize emails based on actual consumer behavior, and use product-based triggers to provide the right offers at the right time. Conversions will follow.
Use data to customize products. Consumers are accustomed to customized experiences, so go one step further than the basics. Don't just state the user's name -- customize the website and service based on actual usage and on-site behavior. Don't waste time with a general list of promotions to boost performance and sales. Offer people products they've expressed an interest in or items that their usage suggests they will like.
Make the most of cross-channel data. Advertising platforms like Facebook and Google AdSense have a look-alike function to help marketers identify new audiences. Finding the right social influencer can be tough, but using a look-alike function to target individuals based on their interests and social interactions couldn't be easier. Use this tool to expand reach and include relevant individuals, such as the audiences of direct competitors.
Leverage guerrilla data. Identify direct competitors and market leaders, and then start tracking their marketing and sales initiatives. Subscribe to newsletters, follow them on social media, read quarterly earnings reports and sign up for a free trial. These are all valuable sources of information on other companies' communication strategies, as well as how they re-engage users and push them through the conversion funnel. Not only will that information save time and money, but it will help detect changes in the market before it's too late.
Related: 10 Elements of a Successful Data-Driven Marketing Strategy
The bottom line: Don't blow the marketing budget on expensive social influencers. Those individuals can be used later as part of a multifaceted strategy. First, focus on getting the data-driven approach right, and keep tracking, learning and expanding.
