Past Advertising Research Articles

“Is It Smart to Be Thrifty?”: How Advertisers Navigated Message Strategies During the Great Depression

ABSTRACTDespite the major historical significance of the Great Depression, little scholarly research exists that analyzes the state of newspaper advertising during the 1930s, particularly in the hard-hit Dust Bowl states. Using Taylor’s six-segment message strategy wheel, this research examined display advertising during one of the most difficult years in the most difficult places: 1934 in the Dust Bowl region of Nebraska, Colorado, Kansas, Oklahoma, New Mexico, and Texas. Results show that essential services, such as banks, utilities, and transportation, primarily used the informational/rational strategy to provide reassurance and empathy to consumers. However, nonessential industries, such as cosmetics, expensive home goods, and tobacco, often used the transformational/sensory approach to encourage high-quality experiences through spending. This historical analysis offers a unique opportunity for contemporary advertisers to understand how past advertising strategies during a crisis influence the present.

МОДЕЛЬНА ОЦІНКА РЕКЛАМНОЇ КАМПАНІЇ В УМОВАХ ІНФЛЮЕНС-МАРКЕТИНГУ

The article is devoted to the analysis of the advertising campaign of influence marketing, which includes the application of the influence of interpersonal communication on the effectiveness of the advertising campaign. An economic-mathematical model of this advertising campaign was composed, an analysis of the campaign that actually took place was performed, conclusions were drawn about the regularities of this campaign, in particular, the preservation of the advertising effect over time was revealed. Further study of advertising campaigns using influence marketing in form of public opinion leader as a paid media and interpersonal communication on social networks as an earned media, was obtained. It was shown how the use of a generalized model of advertising campaign management allows identifying the features of the advertising influence of past advertising campaigns and, with the help of taking into account such features, increasing the effectiveness of the advertising campaign by optimizing the distribution of the advertising budget over time and between different types of advertising.

The Impact of Advertising and R&D on Bankruptcy Survival: A Double-Edged Sword

Advertising and research and development (R&D) benefit firms by increasing sales and shareholder value. However, when a firm is in bankruptcy, the cumulative effects of its past advertising and R&D can be a double-edged sword. On the one hand, they increase the firm’s expected future cash flow, which increases the likelihood that the bankruptcy court will decide the firm can survive. On the other hand, they increase the liquidation value of the firm’s assets, which decreases the likelihood that the bankruptcy court will decide that the firm can survive. The author argues that the ability of advertising and R&D to either increase or decrease bankruptcy survival is contingent on the influence that the firm’s suppliers have, relative to other creditors, on the bankruptcy court’s decision. Advertising and R&D increase (decrease) bankruptcy survival when suppliers have a high (low) level of influence. Empirical analyses, conducted on 1,504 bankruptcies, show that advertising (R&D) increases bankruptcy survival when at least 35%−38% (18%−21%) of the bankrupt firm’s debt has been borrowed from suppliers, whereas it decreases bankruptcy survival below this point. Out-of-sample machine learning validation shows that the ability to predict whether a bankrupt customer will survive is substantially improved by considering the firm’s advertising and R&D.

Enhancing Power of Marketing Experiments Using Observational Data

Advertising experiments often suffer from noisy responses making precise estimation of the average treatment effect (ATE) and evaluating ROI difficult. We develop a principal stratification model that improves the precision of the ATE by dividing the customers into three strata -- those who buy regardless of ad exposure, those who buy only if exposed to ads and those who do not buy regardless. The method decreases the variance of the ATE by separating out the typically large share of customers who buy and therefore have individual treatment effects that are exactly zero. Applying the procedure to 5 catalog mailing experiments with sample sizes around 140,000 shows a reduction of 36-57% in the variance of the estimate. When we include pre-randomization covariates that predict stratum membership, we find that estimates of customers' past response to similar advertising are a good predictor of stratum membership, even if such estimates are biased because past advertising was targeted. Customers who have not purchased recently are also more likely to be in the never purchase stratum. We provide simple summary statistics that firms can compute from their own experiment data to determine if the procedure is expected to be beneficial before applying it.

Bayesian Nonparametric Dynamic Methods: Applications to Linear and Nonlinear Advertising Models

Bayesian methods for dynamic models in marketing have so far been parametric. For instance, it is invariably assumed that model errors emerge from normal distributions. Yet using arbitrary distributional assumptions can result in false inference, which in turn misleads managers. The author therefore presents a set of flexible Bayesian nonparametric (NP) dynamic models that treat error densities as unknown but assume that they emerge from Dirichlet process mixtures. Although the methods address misspecification in dynamic linear models, the main innovation is a particle filter algorithm for nonlinear state-space models. The author used two advertising studies to confirm the benefits of the methods when strict error assumptions are untenable. In both studies, NP models markedly outperformed benchmarks in terms of fit and forecast results. In the first study, the benchmarks understated the effects of competitive advertising on own brand awareness. In the second study, the benchmark inflated ad quality, and consequently, the effects of past advertising appeared 36% higher than that predicted by the NP model. In general, these methods should be valuable wherever state-space models appear (e.g., brand and advertising dynamics, diffusion of innovation, dynamic discrete choice).

NGOs’ Advertising in South Africa and Implications for NGOs in China

In this paper, we discuss NGOs (Non-Governmental Organizations) and NPOs (Non-Profit Organizations) in general and focus on the advertising strategy NGOs should undertake. More specifically, we compare and contrast the NGO history in South Africa and China, its corresponding past advertising, and implications for advertising strategy for Chinese NGOs going forward. This includes a discussion of a key issue of the efficacy of advertising that evokes emotion, and how it can be a “mixed-blessing.” It is suggested that the advertising strategy of South African NGOs can usefully inform NGOs in China.

Exploring Advertising Equity: How a Brand's Past Advertising May Affect Consumer Willingness to Approach Its Future Ads

This article introduces “advertising equity” to denote consumers’ cumulative perceptions of the global value of a brand's past advertising. In five empirical studies we show that advertising equity is a distinct facet of brand equity, not fully captured by established measures of brand equity in terms of brand communication effects and brand loyalty. What is more, advertising equity is found to affect consumer willingness to voluntarily approach advertising for a brand. The findings indicate that advertising equity captures an aspect of brand equity which has not yet been studied and that further research to better capture the concept and its effects is warranted. We conclude by discussing potential implications of advertising equity in terms of advertising budgeting and forecasting, pretesting and evaluations of advertising, as well as negotiating media and co-branding partnerships.

Pooling and Dynamic Forgetting Effects in Multitheme Advertising: Tracking the Advertising Sales Relationship with Particle Filters

Firms often use a pool or series of advertising themes in their campaigns. Thus, for example, a firm may employ some of its advertising to promote price-related themes or messages and other of its advertising to promote product-related themes. This study examines the interdependence that can occur between pairs of themes in a pool (i.e., pooling effects), the impact of these pooling effects on the allocation of advertising expenditures, and the factors that can affect forgetting rates (or, conversely, carry-over rates) in a multitheme advertising environment. The study measures pooling, wear out, and forgetting (carry-over) effects for a campaign that uses five different advertising themes. To obtain these measures, I extend the linear Nerlove-Arrow (NA) (1962) model to a nonlinear model of advertising theme quality and goodwill and estimate the extended model using Markov chain Monte Carlo (MCMC) and particle filtering ideas. Particle filtering belongs to a class of sequential Monte Carlo (SMC) methods designed to estimate nonlinear/nonnormal state space models. Results show that forgetting (or carry-over) rates may be time varying and a function of prior goodwill (past advertising) and other advertising variables. Results show, moreover, that pooling effects can reduce theme wear out and, in turn, significantly improve advertising efficiency.

Optimal Data Interval for Estimating Advertising Response

The abundance of highly disaggregate data (e.g., at five-second intervals) raises the question of the optimal data interval to estimate advertising carryover. The literature assumes that (1) the optimal data interval is the interpurchase time, (2) too disaggregate data causes a disaggregation bias, and (3) recovery of true parameters requires assumption of the underlying advertising process. In contrast, we show that (1) the optimal data interval is what we call unit exposure time, (2) too disaggregate data does not cause any disaggregation bias, and (3) recovery of true parameters does not require assumption of the advertising process but only data at the unit exposure time. These results hold for any linear dynamic model linking sales with current and past advertising.

Goodwill and dynamic advertising strategies

In this paper, we empirically analyze weekly advertising policies of manufacturing firms in consumer goods markets. We assume firms engage in persuasive advertising, thus policies of firms affect the goodwill of a brand. We introduce a demand and a goodwill production function. A simple transformation of the demand function allows us to identify not only the demand parameters but also the parameters of the goodwill production function. We reconstruct the unobserved goodwill levels using these parameters and past advertising levels. We restrict our attention to Markov Perfect Equilibrium (MPE) strategies which are functions of payoff relevant state variables. Without imposing further restrictions on the dynamic competitive environment, we investigate the relationship between observed advertising strategies—which are assumed to be MPE—and payoff relevant state variables by means of several reduced form specifications. The most important determinant of advertising intensity turns out to be goodwill. We demonstrate that controlling for an advertising campaign significantly improves the explanatory power of the model.

Do Ads Influence Editors? Advertising and Bias in the Financial Media

The independence of editorial content from advertisers' influence is a cornerstone of journalistic ethics. We test whether this independence is observed in practice. We find that mutual fund recommendations are correlated with past advertising in three personal finance publications but not in two national newspapers. Our tests control for numerous fund characteristics, total advertising expenditures, and past mentions. While positive mentions significantly increase fund inflows, they do not successfully predict returns. Future returns are similar for the funds we predict would have been mentioned in the absence of bias, suggesting that the cost of advertising bias to readers is small.

Do Ads Influence Editors? Advertising and Bias in the Financial Media

The independence of editorial content from advertisers' influence is a cornerstone of journalistic ethics. We test whether this independence is observed in practice. We find that mutual fund recommendations are correlated with past advertising in three personal finance publications but not in two national newspapers. Our tests control for numerous fund characteristics, total advertising expenditures, and past mentions. While positive mentions significantly increase fund inflows, they do not successfully predict returns. Future returns are similar for the funds we predict would have been mentioned in the absence of bias, suggesting that the cost of advertising bias to readers is small.

Do Ads Influence Editors? Advertising and Bias in the Financial Media

The independence of editorial content from advertisers' influence is a cornerstone of journalistic ethics. We test whether this independence is observed in practice. We find that mutual fund recommendations are correlated with past advertising in three personal finance publications but not in two national newspapers. Our tests control for numerous fund characteristics, total advertising expenditures, and past mentions. While positive mentions significantly increase fund inflows, they do not successfully predict returns. Future returns are similar for the funds we predict would have been mentioned in the absence of bias, suggesting that the cost of advertising bias to readers is small.

Partial carryover of advertising

A model that combines advertising carryover with purchase reinforcement is presented. It accommodates the possibility that certain members of the consumer population rely only on their experience with the product, while others are also affected by past advertising. Empirical results with two product categories indicate that for bimonthly data advertising retention does not exist at all.

Reasoning with empirical marketing knowledge

Expert system development typically requires that a researcher translate domain-specific knowledge into a set of abstract rules describing the relationships between knowledge elements. In marketing, this task has proven to be very difficult. Much of the marketing knowledge is in the form of empirical research rather than generally accepted theories or heuristics. The observed relationships often depend on the research context and these dependencies must be explicitly represented in the rule premises. An alternative approach, described in the present paper, is to represent empirical knowledge in its original context and dynamically abstract the knowledge to analogous new situations. This approach is illustrated with adduce, a frame-based system for reasoning about consumer response to advertising. The system infers how consumers will react to new ads by searching for relevant past advertising experiments and then generalizing research results across similar contexts.

Optimal Advertising with Stochastic Demand

A stochastic, sequential model is developed to determine optimal advertising expenditures as a function of product maturity and past advertising. Random demand for the product depends upon an aggregate measure of current and past advertising called “goodwill,” and the position of the product in its life cycle measured by sales-to-date. Conditions on the parameters of the model are established that insure that it is optimal to advertise less as the product matures. Additional characteristics of the optimal advertising policy are also established.

LYDIA PINKHAM DATA REMODELLED

Abstract. There is no effective bivariate feedback relationship between Lydia Pinkham monthly dollar sales and advertising. The effectiveness is measured in terms of the forecasting performance of the bivariate models against the forecasting performance of the respective univariate models, outside the fit period. While the future advertising is better forecast by using the past advertising and sales, the future sales are better forecast by using past sales only. There is no Koyck effect or memory effect of advertising on sales. The results are completely opposite to the conclusion of the previous researchers.

An Optimum Budget Allocation Model for Dynamic, Interacting Market Segments

This paper formulates a model for determining the optimal allocation of a given advertising budget over M interacting market segments and a time domain of T periods. Guidance for budget size optimization is provided via a shadow price. The basic input parameters are in terms of sales saturation levels and advertising elasticities, concepts experienced advertising executives understand and are willing to estimate. Economic and political developments in Western Europe are increasing the interactions among geographically defined segments, and recent development in discrimination techniques may soon make market segmentation a practical strategy for the United States market. In relation to the time domain, the simplistic and often unrealistic constraint of a constant carryover effect is relaxed in that current advertising is hypothesized to generate sales both by creating new customers and by interacting with the residual effects of past advertising (goodwill) thus reinforcing preferences of past customers. This interactive formulation relating past and future expenditures allows a model user greater flexibility in specifying the relationship between advertising and sales. The mathematical programming technique used is a form of convex programming.

ADVERTISING BY MEDICAL MEN

Medical Journal of AustraliaVolume 2, Issue 6 p. 209-209 Out of the Past ADVERTISING BY MEDICAL MEN First published: 01 August 1958 https://doi.org/10.5694/j.1326-5377.1958.tb67104.xAboutPDF ToolsRequest permissionExport citationAdd to favoritesTrack citation ShareShare Give accessShare full text accessShare full-text accessPlease review our Terms and Conditions of Use and check box below to share full-text version of article.I have read and accept the Wiley Online Library Terms and Conditions of UseShareable LinkUse the link below to share a full-text version of this article with your friends and colleagues. Learn more.Copy URL Share a linkShare onFacebookTwitterLinkedInRedditWechat No abstract is available for this article. Volume2, Issue6August 1958Pages 209-209 RelatedInformation