BUSI 439 Week 5 Group Case Study Project 3 Example

Counting Every Step at Lakeshore Pet Supply: Attribution, Retargeting and the Store Connection

The Business Problem

Lakeshore Pet Supply operates six stores in two states and a website that sells food, toys and supplies for dogs, cats and small animals. Online sales have been flat at about $210,000 a month for a year, while total marketing spending has risen 30 percent. The marketing report, which credits every online sale to the last ad clicked before purchase, shows retargeting ads, the banner ads that follow visitors after they leave the site, producing 34 percent of online revenue at a low cost per sale. On that evidence, the company has doubled its retargeting budget twice. Meanwhile, store managers report that customers often arrive asking whether an item they saw online is in stock, and that many leave when it is not, or never come because they could not tell.

The case therefore presents a contradiction. If retargeting were producing a third of online sales cheaply, doubling it should have raised sales. Roberts and Zahay (2018) stress that marketers must measure the contribution of each channel carefully when customers interact with a brand through many touchpoints online and offline, and Lakeshore's flat sales suggest its measurement is crediting the wrong channel.

The Case Data

Other figures in the case complete the picture. The site converts 1.9 percent of visits; 70 percent of shoppers who view a product page leave without adding it to a cart; only 12 percent of product pages carry any customer reviews; and the website shows no information about store inventory, although the stores' point-of-sale system tracks it daily.

Why the Report Misleads: Attribution

Last-click attribution gives full credit to the final touch. Because retargeting only follows people who have already browsed the store, many of whom would come back and order regardless, these ads tend to collect the final click whether or not they made any difference. Li and Kannan (2014) developed a model for attributing conversions across multiple online channels, including search, email, display and referral, then tested it against a field experiment. Their results showed that the contributions of channels estimated by their model differed considerably from those implied by simple last-click metrics, and that some channels earned far more credit under last-click rules than their true influence on conversion justified, while others, which started customers on the path to purchase, were undervalued.

Lambrecht and Tucker (2013) add a second reason for doubt. Studying a travel website's retargeting campaign in a field experiment, they found that dynamic retargeted ads showing the exact products a consumer had viewed were, on average, less effective than generic brand ads, and that they became more effective only when consumers had already narrowed their preferences, for example after visiting a review site. Lakeshore's retargeting shows each visitor the exact items viewed, regardless of how far the visitor has progressed in the decision.

Together, the studies suggest that Lakeshore's retargeting is claiming credit for many sales that would have happened anyway, while its paid search and social ads, which introduce new customers, may be undervalued.

The Missing Store Connection

The second problem lies between the website and the stores. Gallino and Moreno (2014) studied a retailer that began showing reliable store inventory information on its website through a buy-online, pick-up-in-store option. They found that after the change, online sales in the areas near stores decreased while store sales and store traffic increased, as customers who could confirm availability chose to buy in person, often purchasing additional items. For Lakeshore, whose customers frequently need pet food the same day, store availability is exactly the information they seek. Without it, the website sends shoppers to stores uncertain, and some go to competitors instead.

The Missing Reviews

The third problem is on the product pages. Ludwig et al. (2013) studied reviews and conversion rates on an online bookseller's site and found that the emotional content of reviews affected conversion rates, with increases in positive emotion raising conversion at a decreasing rate, and that reviews whose linguistic style matched the style typical of the product's interest group also helped convert visitors. With reviews on only 12 percent of pages, most Lakeshore shoppers see nothing from other pet owners, and pet owners often trust other owners' experiences with food and toys over a seller's description.

What the Customer Path Really Looks Like

The case's loyalty records show how Lakeshore customers actually shop. A typical new dog owner first finds the company through a search for a food brand or a puppy supply list, reads a few product pages, leaves, receives an email after signing up for a first-order discount, returns through a retargeting ad a few days later and buys, often by driving to a store. Under last-click rules, the search that started the relationship and the email that kept it going earn nothing, the retargeting ad earns the whole online sale, and the store purchase is not connected to the website at all. Multiplied across thousands of customers, that pattern explains how a report can praise retargeting while sales stay flat. It also shows why the team's strategies treat measurement, the website and the stores as one problem rather than three separate ones.

Problem Statement

Lakeshore Pet Supply measures marketing with last-click reports that overcredit retargeting, so it is moving its budget toward the channel least likely to bring new sales, while its website hides the store inventory and customer reviews that would convert shoppers online and in person.

Conversion and Optimization Web Strategy

Measure Retargeting's True Effect, Then Rebalance

Lakeshore will run a holdout test: for six weeks, a random 20 percent of site visitors will be excluded from retargeting, and their purchase rate will be compared with that of visitors who see the ads. The difference is the sales retargeting truly adds. Retargeting will also be changed to follow the research: generic brand ads for visitors early in the decision, and product-specific ads only for visitors who have viewed reviews or compared several items. Budget freed by the test will move to paid search for new customers and to email.

Adopt Multi-Touch Attribution

The company will replace last-click reports with an attribution model that credits each channel's contribution to the path, starting with a simple position-based model and refining it with the holdout results and future tests, in the spirit of the validated approach developed by Li and Kannan (2014). Store sales by customers identified through loyalty accounts will be linked to their online visits.

Show Store Inventory and Offer Pickup

Every product page will show availability at the shopper's nearest store, updated daily from the point-of-sale system, and shoppers will be able to reserve items for pickup within two hours. Store staff will place reserved orders at a pickup counter near add-on items such as treats and toys.

Gather and Display Reviews

Every online and loyalty customer will receive a review request ten days after purchase, and store receipts will invite reviews by text message. Reviews will appear near the top of each product page, and the company will feature reviews that describe a pet's experience in the owner's own words.

Measurable Results

A report that credits the last click will always favor the ad that follows a shopper to the checkout, whether or not that ad changed anything.

Testing Plan

The holdout test comes first, because every later budget decision depends on knowing what retargeting truly adds. The review requests and inventory display can be introduced at the same time, but inventory display will be launched in three stores' areas first, with the other three serving as a comparison, so the company can measure its effect on store traffic and online sales separately, as Gallino and Moreno (2014) did. Reviews will be tested by comparing conversion on pages that gain five or more reviews with similar pages that have not yet gained them. Every test will be judged on combined online and store revenue rather than on online sales alone, since the research suggests some sales will move from the website to the stores.

Risks and Limits

Showing inventory may reduce online sales as some shoppers choose pickup, which could alarm managers who read only the online report; for that reason the plan measures combined revenue. Inventory data that is wrong is worse than none, so availability will show only for items whose counts the stores confirm daily. Linking store purchases to online visits depends on loyalty accounts, which capture about 60 percent of store sales in the case, so the link will undercount the website's influence; the team treats the figure as a floor, not a full measure. The holdout test sacrifices some retargeting during six weeks, which may cost a small number of sales if retargeting does work, a cost worth paying to learn its true effect.

Role Rotation and Lessons

Casey Morgan led this final project, Jordan Ellis edited it and Avery Brooks served as Technical Writer, so each member has now held every role. The team's main lesson across the three cases is that the case data must be questioned as well as used: the first case hid its problem in a single checkout step, the second in two stages of a funnel and the third in the method behind the marketing report.

Conclusion

Lakeshore's flat sales despite rising spending point to a measurement problem disguised as a marketing success. By testing what retargeting truly adds, moving to multi-touch attribution, showing store inventory online and gathering reviews, the company can spend its budget on channels that create sales and convert more of the shoppers it already attracts, both online and in its stores.

References

Gallino, S., & Moreno, A. (2014). Integration of online and offline channels in retail: The impact of sharing reliable inventory availability information. Management Science, 60(6), 1434-1451. https://doi.org/10.1287/mnsc.2014.1951

Lambrecht, A., & Tucker, C. (2013). When does retargeting work? Information specificity in online advertising. Journal of Marketing Research, 50(5), 561-576. https://doi.org/10.1509/jmr.11.0503

Li, H., & Kannan, P. K. (2014). Attributing conversions in a multichannel online marketing environment: An empirical model and a field experiment. Journal of Marketing Research, 51(1), 40-56. https://doi.org/10.1509/jmr.13.0050

Ludwig, S., de Ruyter, K., Friedman, M., Brüggen, E. C., Wetzels, M., & Pfann, G. (2013). More than words: The influence of affective content and linguistic style matches in online reviews on conversion rates. Journal of Marketing, 77(1), 87-103. https://doi.org/10.1509/jm.11.0560

Roberts, M. L., & Zahay, D. (2018). Internet marketing: Integrating online and offline strategies (4th ed.). Cengage Learning.