Advertising as we know these days have changed so much from what it used to be a decode ago. First thing any marketing manager thinks of when it comes to devising a marketing strategy is to figure out the online advertising channels. But is it really bring in money? How much of the money invested in online advertising is actually getting converted to sales revenue? Paul R. Hoban and Randolph E. Bucklin, analyzed this same concept in a paper that we are going to dig deeper in this blog post.

Challenge with the study:

The main challenge in studying the effects of online ads on consumers is there is a widespread selection effect. Users browsing patterns and their preferences affect the impact of the advertising. To overcome these selection bias, the paper focuses on profitability or conversion during the purchase funnel. The life cycle of the user follows the four different stages: Non visitor, visitor, registered user and converted customer.

Method:

The method used here is to have two different groups: Control and Treatment group. Control group have similar ad displays as that of the treatment group, but their ads are of some charity firm whereas the treatment group had a focused firm for advertising. This is to help control the selection bias. During the experiment, for the first digital interaction the users were randomly selected into one of the two groups.

Findings from the experiment:

Based on the experiment, they have found the effectiveness for various stages of the users as follows:

Non Visitor: Helps in creating the brand image since the user has never visited the brand’s website. Here the ads
have a little effect in conversions.

Visitor: Users who have already visited the site before and had not created registered accounts, seeing the online ads will have little or no effect. If they hadn’t done that previously, there is a very little chance the ads will trigger them to do.

Registered Users: On the other hand, for registered users, the ads might trigger an emotion motivating them to make a purchase and in that case they have a good effect in conversion rates.

Converted Users: People who had already made a purchase with the brand, the ads might serve as a memory but might not have an effect in making them purchase again. There was no clear result obtained from the paper about the converted users.

Conclusion:

The experiment showcased how the online advertising will impact different customer group segments. By leveraging this and varying the frequency and carryover effects we can increase the marginal effects of exposure. For example, this effect is more prominent for non visitors and less prominent for already converted users. The main limitation of this paper is that the experiment is carried out only for one particular firm. So the results can’t be generalized. There could be same users opening multiple browsers viewing similar ads. That might hinder the estimation. Thus this paper provides numerous opportunities for further research in this domain.

References:

Paul R. Hoban Randolph E. Bucklin February 2015, “Effects of Internet Display Advertising in the Purchase Funnel: Model-Based Insights from a Randomized Field Experiment”

Manchanda, Puneet, Jean-Pierre Dubé, Khim Yong Goh, and Pradeep K. Chintagunta (2006), “The Effect of Banner Advertising on Internet Purchasing,” Journal of Marketing Research, 43 (1), 98-108.