Measuring Multi-Channel Advertising Response

Zantedeschi, Daniel; Feit, Elea McDonnell; Bradlow, Eric T.

doi:10.2139/ssrn.2720615

Cited by 9 publications

(9 citation statements)

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“…The AS ibmt covariates in the second term of Equation 5 relate to advertising exposures or clicks, depending on the medium. Because advertising has previously been shown to have carryover effects (Leone 1995), we accommodate this phenomenon by replacing advertising exposure/click variables with ad stock ( AS ) variables, as previously employed by Danaher and Van Heerde (2018), Dinner, Van Heerde, and Neslin (2014) and Zantedeschi, Feit, and Bradlow (2017). Our measure of ad stock, defined separately for each medium m , is 12…”

Section: Modelmentioning

confidence: 99%

“…Table 3 summarizes the potential sources of endogeneity and how we propose to handle them. The first possible source of endogeneity is due to targeting, and the two media most likely to suffer from this are email and catalogs because they are directly controlled by managers responsible for sending messages to consumers (Zantedeschi, Feit, and Bradlow 2017). A second potential source of endogeneity arises from paid search advertising, whereby customers signal their interest in a brand or product category by initiating online search, a form of self-selection (Blake, Nosko, and Tadelis 2015; Narayanan and Kalyanam (2015).…”

Section: Modelmentioning

confidence: 99%

“…Given the large number of weeks in which there are no purchases by an individual, we follow Zantedeschi, Feit, and Bradlow (2017) and use a Tobit model for sales. In this model,…”

Section: Modelmentioning

confidence: 99%

See 2 more Smart Citations

Advertising Effectiveness for Multiple Retailer-Brands in a Multimedia and Multichannel Environment

Danaher¹,

Danaher²,

Smith³

et al. 2020

Journal of Marketing Research

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An important aspect of multimedia advertising effectiveness that remains unexplored is a customer-level analysis of the relative importance of each medium for multiple retailer-brands within a product category. The increasing availability of customer databases for parent companies containing multimedia ad exposures, sales transactions in several purchase channels, and information across multiple retailer-brands now allows for a broader examination of advertising effectiveness. In this research, the authors monitor 4,000 customers over two years, linking their exposure to three media (email, catalogs, and paid search) to their in-store and online purchases for three retailer-brands in the clothing category. They develop a Tobit model for sales response to multimedia advertising that captures within-brand and within-channel correlations and accommodates individual-level advertising response parameters. Due to the very large number of observations (2.4 million) and random effects (60), the authors employ an emerging machine learning technique, variational Bayes, to estimate the model parameters. They find that email and sometimes catalogs from a focal retailer-brand have a negative influence on other retailer-brands in the category, whereas paid search influences only the focal retailer-brand. However, competitor catalogs often positively influence focal retailer-brand sales, but only among omnichannel customers. They segment customers by retailer-brand and channel usage, revealing a sizeable group of customers who shop across multiple retailer-brands and both purchase channels. Moreover, this segment is the most responsive to multimedia advertising.

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Section: Modelmentioning

confidence: 99%

Section: Modelmentioning

confidence: 99%

See 1 more Smart Citation

Advertising Effectiveness for Multiple Retailer-Brands in a Multimedia and Multichannel Environment

Danaher¹,

Danaher²,

Smith³

et al. 2020

Journal of Marketing Research

View full text Add to dashboard Cite

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“…In addition, Dalessandro et al (2012) shows through simulation that using the Shapley value can approximate the causal effect of different channels. Finally, Zantedeschi et al (2015) and Barajas et al (2016) show how challenging the attribution problem is even when collecting data using an experiment. The latter paper also finds that impressions with high baseline of conversions would be allocated by a publisher to an advertiser even though this allocation may be inefficient.…”

Section: Related Workmentioning

confidence: 99%

Beyond the Last Touch: Attribution in Online Advertising

Berman

2018

Marketing Science

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Online advertisers often utilize multiple publishers to deliver ads to multi-homing consumers. These ads often generate externalities and their exposure is uncertain, which impacts advertising effectiveness across publishers. We analytically analyze the inefficiencies created by externalities and uncertainty when information is symmetric between advertisers and publishers, in contrast to most previous research that assumes information asymmetry. Although these inefficiencies cannot be resolved through publisher side actions, attribution methods that measure the campaign uncertainty can serve as an alternative solution to help advertisers adjust their strategies. Attribution creates a virtual competition between publishers, resulting in a team compensation problem. The equilibrium may potentially increase the aggressiveness of advertiser bidding leading to increased advertiser profits. The popular last-touch method is shown to over-incentivize ad exposures, often resulting in lowering advertiser profits. The Shapley value achieves an increase in profits compared to last-touch. Popular publishers and those that appear early in the conversion funnel benefit the most from advertisers using last-touch attribution. The increase in advertiser profits come at the expense of total publisher profits and often results in decreased ad allocation efficiency. We also find that the prices paid in the market will decrease when more sophisticated attribution methods are adopted.

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“…Li and Kannan (2014) introduced a methodology to access the value from a variety of marketing channels such as referral, email, displayed, and paid search in an online environment. Zantedeschi, Feit, and Bradlow (2015) proposed a hierarchical Bayesian model for measuring multi-channel advertising response. Yadagiri, Saini, and Sinha (2015) developed non-parametric and semi-parametric approaches to estimate the value contributed from different marketing channels.…”

Section: Literature Reviewmentioning

confidence: 99%

Multi-Click Attribution in Sponsored Search Advertising: An Empirical Study in Hospitality Industry

Anderson

Cheng

2017

Cornell Hospitality Quarterly

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Sponsored search advertising has become a dominant form of advertising for many firms in the hospitality vertical, with Priceline and Expedia each spending in excess of US$2 billion in online advertising in 2015. Given the competition in online advertising, it has become essential for advertisers to know how effectively to allocate financial resources to keywords. Central to budget allocation for keywords is an attribution of revenue (from converted ads) to the keywords generating consumer interest. Conventional wisdom suggests several ways to attribute revenues in the sponsored search advertising domain (e.g., last-click, first & last-click, or evenly distributed approach). We develop a multi-click attribution methodology using a unique multi-advertiser data set, which includes full advertiser and consumer-level click and purchase information. We add to the literature by developing a two-stage multiclick attribution methodology with a specific focus on sponsored search advertising in the hospitality industry with which we develop a parametric approach to calculate the value function from each stage of the estimation process. Given our multi-advertiser data set, we are able to illustrate the inefficiency of single-click attribution approaches, which undervalue assist clicks while overvaluing converted clicks.

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Measuring Multi-Channel Advertising Response

Cited by 9 publications

References 0 publications

Advertising Effectiveness for Multiple Retailer-Brands in a Multimedia and Multichannel Environment

Advertising Effectiveness for Multiple Retailer-Brands in a Multimedia and Multichannel Environment

Beyond the Last Touch: Attribution in Online Advertising

Multi-Click Attribution in Sponsored Search Advertising: An Empirical Study in Hospitality Industry

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