Effective Design of Influencer Marketing Campaign in Social Networks

Rakesh Mallipeddi, Subodha Kumar, Chelliah Sriskandarajah, Yunxia Zhu

For a long time, firms have relied on opinion leaders (who influence other individuals by sharing their experiences) to market their products. Similarly, with the rapid growth in the number of users of social media platforms, such as Facebook, Instagram, LinkedIn, and Twitter, firms have turned to influencers on these platforms to market their products. A survey conducted by the Influencer Marketing Hub (2022) reports that the market size of influencer marketing has increased from $1.7 billion in 2016 to nearly 13.8 billion in 2022, and almost 75% of the respondents to the survey plan to run influencer marketing campaigns.

With thousands of influencers to choose from, a question of importance to a firm is: given a limited budget, how to design its influencer marketing campaign? More specifically, designing a successful marketing campaign entails selecting an optimal subset of influencers for promoting the firm’s products. Furthermore, when influencer marketing campaigns run for longer time periods, besides selecting influencers, scheduling influencers' ads over the campaign is crucial.

A recent Management Science paper titled “A Framework for Analyzing Influencer Marketing in Social Networks: Selection and Scheduling of Influencers” develops a data-driven modeling framework to help a firm successfully conduct (i) short-horizon and (ii) long-horizon influencer marketing campaigns, for which two models are developed, respectively, to maximize the firm’s benefit. The models are based on the interactions with marketers, observation of firms’ message placements on social media, and model parameters estimated via an empirical analysis conducted using data from Twitter.

Their empirical analysis discovers the effects of the collective influence of multiple influencers and finds two critical parameters to be included in the models, namely, the multiple exposure effect and the forgetting effect. The multiple exposure effect refers to the curvilinear effect of additional exposure of an ad on a customer’s engagement with the ad. The forgetting effect is the impact of the gap between two consecutive ads on customer engagement, which is an important factor to consider when designing long-horizon marketing campaigns.

To design short-horizon influencer marketing campaigns, they develop an optimization model to select influencers. While solving this problem is computationally hard, the authors used a mathematical programming procedure to provide near-optimal solutions to select influencers for the campaign. In addition, the paper demonstrates the economic significance of the peer effect (i.e., the influence of a follower on another follower of an influencer). The benefit loss from ignoring the peer effect is particularly significant when the online network has a high number of connections among followers. Furthermore, the paper also demonstrates that selecting influencers for your campaign based on the number of their followers is not always the best strategy.

Long-horizon influencer marketing campaigns (appropriate for brand building) require a careful selection of influencers and a scheduling plan to sequence the ads throughout the campaign, which may last several weeks or months. The authors develop an efficient procedure that simultaneously selects influencers for the campaign and provides a schedule to sequence influencers’ posts. Further analysis of long-horizon campaigns shows that the net benefit obtained by the firm is concave as a function of increasing budget level, i.e., the firm’s benefit first increases at a diminishing rate with a higher budget allocated to the campaigns and then starts to decrease. This highlights the need to determine the budget allocated to the influencer marketing campaigns strategically. In addition, they also show that choosing a random scheduling strategy could lead to sub-optimal performance of the influencer marketing campaign.

On-time delivery is not good enough – Study shows online retailers should also show their efforts for fast deliveries

Xingzhi Jia, M. Serkan Akturk, Rakesh Mallipeddi

While customers expect fast and on-time deliveries when they purchase online, delivery delays are inevitable, especially in periods of disruption such as demand surges during the holiday season. Customers are always eager to receive their orders on time, and most have grown used to track the status of their orders on the seller’s website while the order is still being processed. Major retailers such as Amazon and Walmart have made massive investments in related technologies to provide order status updates to customers. Nowadays, however, smaller online retailers relying on third-party logistics partners (3PL) can easily do the same thing through a wide selection of cloud-based, ready-to-use solutions such as ClickPost, LateShipment, and many others.

A study published in the Journal of Operations Management examines how giving customers the ability to track online orders can impact customer satisfaction. Using data from a major online retailer, the study found that on-time delivery is no longer the only issue that will affect customer satisfaction when an online retailer allows customers to track their orders. Instead, even if online orders are delivered on time, customers may still feel dissatisfied if the online retailer took too long to process their orders before handing them over to its logistics partner (3PL) for delivery. Such a negative impact on customer satisfaction is more severe compared to when the 3PL partner took too long to deliver the packages. This is because customers think that the retailer is the one to blame when it could not process the orders for shipping promptly after receiving them from customers.

The study’s findings show that allowing customers to track the status of online orders before they receive the packages can expose potential deficiencies within an online retailer’s internal order fulfillment process. This impact on customer satisfaction exists regardless of whether the order was eventually delivered late or early. Thus, while it is intuitive that timely deliveries are important for customer satisfaction, customers also expect to see online retailers’ efforts to promptly process their orders when checking the status of their orders online.

The study offers several recommendations for online retailers to improve customer satisfaction. First, online retailers that allow customers to track order status should prioritize improving their internal operations (such as order picking and packaging) so that orders are processed as fast as possible. They can also ask customers to review a product itself and its delivery separately so that dissatisfaction caused by order fulfillment delays will be less reflected in the product reviews.

Second and more importantly, customers may already feel dissatisfied when they check the order status and observe a delay, even without knowing if the order will actually arrive late. Borrowing a central idea from service recovery research, which emphasizes the importance of addressing the problem promptly, online retailers should actively reach out to customers when the order processing time is longer than usual. In such a case, a message to the customers stating that “there is a slight delay in processing the order, but you can expect the delivery on time” may go a long way in mitigating potential dissatisfaction caused by delays in internal order processing. Finally, the study finds that the positive impact of early delivery (delivering packages before the promised date) on satisfaction is minimal, compared to the negative impact of late delivery. Thus, online retailers should also under-promise when estimating the time, they will take to process the orders to avoid showing any internal delays on the order status page.

By taking these steps, online retailers can improve customer satisfaction and ensure they’re meeting customer expectations around product delivery.