Social Media and Online Reviews Can Drive Sales, But Counting the Impact Requires More Than Likes

Research shows that influencers, customer recommendations and online reviews can affect purchases and revenue, while revealing the many substantial gaps in how companies measure their contribution.

By Bruce Bolger

How Much Do Influencers Affect Sales?
Online Reviews Can Affect Both Discovery and Purchasing
Referrals Need Their Own Measures
Companies Can Track the Activity, but Measurement Remains Uneven
The Essential Question: How Much Additional Business Was Created?

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Instagram and TikTok influencers, customer referrals, and Google and Yelp reviews can influence what people buy, but research offers no universal percentage of brand sales attributable to these sources. Studies document meaningful revenue effects in specific settings, show why the most visible influencers do not necessarily deliver the best returns, and demonstrate that generating referrals and converting them into purchases require different approaches. Companies can track much of this activity, although establishing how much additional business it creates requires connecting marketing data with transactions and testing what would have happened without the campaign. Notably, the best measurement begins once one has gained permission to communicate over time through social media or e-mail.

How Much Do Influencers Affect Sales?

A broad assessment comes from Meizhi Pan, Markus Blut, Arezou Ghiassaleh and Zach W. Y. Lee’s “Influencer Marketing Effectiveness: A Meta-Analytic Review”, published online in 2024 and in the 2025 volume of the Journal of the Academy of Marketing Science. Synthesizing 1,531 effects from 251 papers, the authors identify effects on attitudes, engagement, purchase intentions and actual purchasing behavior. Effectiveness varies with the influencer, audience, content, platform and product. The review also calls for more research on transactional outcomes such as sales and return on investment, an important limitation when interpreting claims about influencer effectiveness.

Research that follows transactions provides more concrete guidance. In “Revenue Generation Through Influencer Marketing”, published in the Journal of Marketing in 2024, Maximilian Beichert, Andreas Bayerl, Jacob Goldenberg and Andreas Lanz examine the journey from followers to reach, engagement and revenue, including endorsement costs. In their American Marketing Association research summary, the authors report that influencers with smaller followings were more cost-effective in generating revenue than their larger counterparts. The implication is that brands should evaluate the relevance and purchasing behavior of an audience alongside its size; the finding does not establish that small influencers always outperform large ones.

TikTok research also challenges the assumption that entertaining content necessarily sells the featured product. Jeremy Yang, Juanjuan Zhang and Yuhan Zhang’s “Engagement That Sells: Influencer Video Advertising on TikTok”, published online in 2024 in Marketing Science, links influencer videos with product sales on Taobao in China. Their analysis finds that a measure of engagement focused on the product itself predicts sales lift. A viewer may enjoy a creator or a video without becoming interested in buying. Because the research concerns a Chinese commerce setting, its results should inform testing rather than be treated as a sales forecast for a US Instagram or TikTok campaign.

Online Reviews Can Affect Both Discovery and Purchasing

A frequently cited study of reviews and revenue is Michael Luca’s “Reviews, Reputation, and Revenue: The Case of Yelp.com”, a Harvard Business School working paper revised in 2016. Using Washington State restaurant revenue records and Yelp’s rating-rounding thresholds, Luca estimates that a one-star increase in Yelp rating leads to a 5%–9% increase in revenue for independent restaurants. He finds no corresponding effect for chain-affiliated restaurants, suggesting that reviews are especially valuable when consumers have less established information about a business. This is evidence from a particular industry and period, rather than a percentage applicable to every brand or review platform.

Research from Northwestern University’s Medill Spiegel Research Center offers another indication of the potential scale. In its analysis of online retail purchase behavior, the purchase likelihood for a product with five reviews was 270% greater than for a product with none. That is a relative increase in purchase likelihood, not a 270-percentage-point gain or evidence that a company’s total sales will rise by that amount. The research also finds diminishing returns as review counts grow and a greater conversion impact for higher-priced products.

Google reviews have a further potential effect through visibility. Google’s local-ranking guidance states that review volume and positive ratings can help a business’s local ranking, alongside other factors such as relevance and distance. Reviews can therefore contribute to a business being discovered as well as evaluated. Google’s guidance does not assign a revenue increase to an additional star, and the Yelp finding should not be transferred to Google as if the two platforms produced identical results.

Referrals Need Their Own Measures

Social media can distribute personal recommendations at scale, but getting someone to share and getting a recipient to buy are separate outcomes. A randomized field experiment published in Management Science involving more than 75,000 customers of an online daily-deal platform found that small changes in referral messages produced different results. Adding information that the sender had purchased increased recipients’ likelihood of buying, while adding information about referral rewards increased subsequent referrals. Combining both pieces of information improved neither outcome.

The practical lesson is to measure the full referral process: how many customers recommend the company, how many recipients respond, how many buy, and whether those buyers return. Shares and invitations reveal distribution; transactions and repeat purchases reveal commercial value. The experiment supports testing message design rather than assuming that more incentives or more information will automatically produce better results.

Companies Can Track the Activity, but Measurement Remains Uneven

The technology for tracking is readily available. Google Analytics campaign parameters identify traffic arriving through tagged links. Combined with properly configured purchase tracking, influencer-specific links, referral identifiers and promotional codes can connect some visits and transactions to a campaign. Companies can extend the analysis through customer relationship management and transaction systems to examine qualified leads, repeat purchases and customer value.

For local businesses, Google Business Profile performance reports include website clicks, direction requests and clicks on the call button. These are useful indicators of customer interest, but a direction request does not establish that someone visited, and a call-button click does not establish that a sale occurred. Likewise, profile activity does not isolate the contribution of reviews from the listing’s other information.

How well do businesses put these pieces together? Nielsen’s 2024 Annual Marketing Report found that only 38% of surveyed marketers evaluated the combined return on traditional and digital marketing. The survey covered marketers managing budgets of at least $1 million and was conducted in December 2023. It is evidence of a broader measurement gap among substantial advertisers, rather than a direct estimate of how many companies accurately measure influencers or reviews.

The Essential Question: How Much Additional Business Was Created?

A transaction credited to social media is not necessarily a transaction caused by it. Consider a hypothetical customer who sees an Instagram video, reads Google reviews, receives a friend’s recommendation and then purchases through a search advertisement. A report assigning all credit to the final click overlooks earlier influences. Conversely, crediting a sale to an influencer code may overstate the effect if the customer already intended to buy.

Companies can address this through experiments comparing outcomes for a campaign group with a suitable control group. Meta’s measurement training describes conversion-lift and geographic testing as ways to assess conversions missed or miscredited by attribution models. Such tests require enough transactions, appropriate controls and a suitable observation period; smaller businesses may need to combine imperfect tracking with customer surveys and cautious comparisons over time.

For enterprise stakeholder management, these findings suggest that online reputation belongs in the discussion of operating performance as well as marketing. Customer experiences provide the substance of reviews and recommendations, while employees and partners help deliver those experiences. A useful management approach connects what people say with service issues, purchasing behavior, retention and profitability. The objective is to understand which relationships and activities create additional, sustainable business—and use that information to improve both the experience and the return.

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Contact: Bruce Bolger at TheICEE.org; 914-591-7600, ext. 230.