Influencer Marketing in a Data-Driven World

Influencer marketing isn’t going anywhere. The industry didn’t just survive COVID-19, it thrived ‘and it’s bigger than ever. The valuation of influencer marketing is projected to hit $13.8 billion in 2021, a 700% increase from 2016. But explosive growth creates big problems for brands. Fortunately, there’s one solution that can revolutionize your whole approach.

What makes a perfect influencer marketing strategy? First, it’s choosing the right influencers for your brand. Easier said than done. But even the right influencer is useless without authentic integration of your product or service. Additionally, without measuring campaign performance correctly you won’t know what went right or wrong anyway. A data-driven approach can fix all of these problems.

Find out why influencer marketing data and analytics should be the cornerstone of your influencer marketing strategy in 2021.

Leveraging data in your influencer marketing strategy

Data is critical to success at every stage of your influencer marketing strategy ‘and its impact stretches beyond just current campaigns. Data enables you to learn from past campaigns, and predict the success of future ones. Big data in influencer marketing creates a snowball effect where you learn exactly what works and what doesn’t.

Let’s explore three influencer marketing problems where adopting a data-driven approach can help:

1. Identifying the right influencers

The perfect branded content is useless if you’re using the wrong influencer for your audience. In fact, 34% of brands running campaigns in-house ranked finding the right influencers as their most significant challenge. Despite the number of influencer marketing platforms ever-increasing, the problem of identifying the right influencer remains ‘especially if you’re doing it manually. This is where data science comes in.

Brands can leverage big data in marketing to identify the optimal influencers for each campaign. It’s common knowledge to look for a dedicated, highly-engaged audience when you’re identifying influencers ‘think consistent views, likes, and comments. But an engaged audience doesn’t always translate to positive brand awareness and sales.

A data-driven approach utilizes conversion rates to determine what specific products and services sell well with a particular audience and which don’t. This data allows you to pinpoint the optimal influencers for your brand. The demographics of an audience ‘such as age, region, interest ‘are vital to influencer campaigns. Like conversion rate data, demographics filter out the irrelevant, meaning you focus exclusively on audiences bringing the most value. It’s this level of specificity that can make or break your influencer marketing campaigns.

Influencer marketing data has uncovered insights we simply wouldn’t have otherwise, such as the phenomenon of super spreaders . Super spreaders are individuals determined to be the most connected influencers in a network. They may not be the biggest influencer individually, but their place in the influencer network allows you to unlock enormous collective reach. Super spreaders are identified using data-driven graph theories and enabled Coca-Cola to generate an impressive 8% average engagement rate.

Once your audience is nailed down, it’s time to start optimizing your brand messaging.

2. Creating content that performs well

You’re probably sick of hearing it, but content truly is king. Data helps you identify the right influencers, but that’s useless if your branded content is all wrong. Internet trends come and go rapidly. What may have been a huge success last year could be a spectacular failure now. Keep an eye on 2021 influencer marketing trends to ensure your influencer marketing strategy isn’t outdated.

Based on data from analytical tools, you can see exactly what’s trending in your niche. Let’s take YouTube for example. YouTube is the second biggest search engine in the world. Influencer marketing data and analytics monitor what keywords your audience is searching YouTube for. A 75% drop in keyword searches tells you a topic that exploded in popularity a few months ago is losing relevance rapidly. Similarly, if a topic’s keyword searches have remained steady for the past 4 years then it could be ripe for evergreen branded content.

Influencer marketing data allows you to track these keywords in real-time and determine whether audience demand is high enough to integrate your brand. Check out Clootboost’s complete guide to YouTube sponsored content to learn what specific integration is best for you.

Data doesn’t only help with current campaigns. It’s the post-integration analysis you unlock which has a massive compounding effect on your future campaigns. Influencer marketing big data and analytics is continuously learning and optimizing, which optimizes your campaigns in turn.

3. Measuring the performance and ROI of influencer marketing

According to MediaKix, measuring return on investment (ROI) is the biggest problem when working with influencers. Historically, empty metrics’ such as impressions were used to determine success. Impressions account for how many people potentially saw your content ‘but this is deceptive. A high impressions count means nothing if the audience didn’t acknowledge or engage with your content. So what’s the alternative? Data.

Impressions and other vanity metrics have been replaced by concrete indicators of audience interest. Influencer marketing analytics allows you to track view duration, likes, comments, and shares ‘all at scale. It’s typical to combine these numbers to form an overall engagement rate percentage. Engagement rate isn’t only a succinct indicator of an influencer’s reach; it allows you to better communicate your work to other departments ‘especially those in charge of budgets! These metrics are fantastic indicators of brand awareness, but data science goes even further. Measuring sales lift in influencer marketing used to be a real grey area for brands, often being the key turn-off for many. Fast-forward to 2021 however, and we have incredible insight.

A Forbes influencer marketing study explored how big data and analytics directly impacts sales at scale. Leveraging loyalty card data, audiences exposed to influencer content spent an incremental $639,700 more than audiences not exposed. Promo codes tailored to specific influencers are also a great method to track ROI. For example, a rice brand used influencer marketing to drive a 44.8% coupon redemption rate, versus a historical rate of just 15%.

Unique promo codes are just one example of a key metric you should be tracking. Another essential KPI is click-through rate (CTR). CTR data is a clear way of seeing what users went beyond a like or comment and actually visited your site. This data can then be leveraged across the whole marketing department, utilizing tactics such as retargeting.

Pixel data is tackling the issue of how digital influencer marketing campaigns impact in-store sales. Forbes‘ study reported that 48% of consumers exposed to influencer content visited the retailer associated with their content within four days. In contrast, the group not exposed to influencer content reported a 29% visit rate, demonstrating a huge jump. As you can see, a data-driven approach to influencer marketing is truly all-encompassing.

Gone are the days of guesstimates and impressions determining the success of your influencer marketing strategy. Leveraging influencer marketing data and analytics to measure impact on sales is transformative ‘and its accuracy is ever-increasing. Combining big data and brand awareness metrics such as view time, likes and shares allows you to execute an influencer campaign with incredible confidence.