Hello, we have won the client's tender to manage contextual advertising for an online store of gardening equipment and household goods. Having a cottage means dealing with snow in winter, planting in spring and gardening in summer: the demand changes as quickly as the seasons.
The challenge of this rapid demand fluctuation is to keep up with tracking product category profitability and adapting accordingly, at least not to launch lawn mowers in winter! :)
I think we won the tender because we offered a market volume forecast by the main product categories and market elasticity as a function of cost of coverage. The client liked that.
We forecast the seasonality of product categories based on historical data.
Click on the image to enlarge.
Based on the seasonality, we time the product launches by category.
Price is one of the main factors that affects conversion of a web-site into sales. We parsed prices from competitors' sites and compared ours with the median to make sure that we are in the market.
We transfer the main indicators to Google Sheets to be able to comment on the same files and observe the trends together with the client.
The client did not really want to disclose sales data, but to exemplify we can show the number of leads per month for one of the categories.
It's hard to say whether it got better or worse, since there were no advertising campaigns before us.
In our experience, automated campaigns bring up to half of the revenue with small investments, so we launch them first.
The main issue with end-to-end analytics was a large outflow of site visitors to offline stores, that is, users found the products on the site and went to one of the offline stores to see the products and get a feel for the tools in person.
There are solutions for tracking the customer online-to-offline flow via loyalty cards, but these are quite expensive and time consuming to implement. So for a start, we decided to use a shortcut, especially considering that the client was not so interested in the complicated solution. We simply tracked the clicks on the store contacts page, since before visiting the store, the user clearly needs to check its address.
Next, we manually compared sales and our synthetic KPI with breakdown by product categories to understand how online store affects revenue in offline stores. Admittedly, the correlation was not convincing but it was there.
In order not to delay the launch of campaigns and avoid the client asking "How many clicks did we have today?", at the start I took an hour to make a simple report in DataStudio
Further, I developed the report by adding new sections, for example, a a breakdown by product categories with their respective trends.
After several years of cooperation, the client moved marketing in-house: we prepared documentation and guides for managing advertising campaigns.
«We started working with the agency in April 2018, the project team suggested we launch the categories of goods in sequence over the season in step with demand growth during the summer. One of our problems is that we have several offline stores for which we could not measure return on advertising investments. To solve this problem, we implemented call tracking, set up goals on the site and manually tracked the revenue trends by categories to collect the overall data and calculate the acceptable cost per lead by category. In general, I consider the task accomplished, we continue to work, I can recommend the team.»
Online store for baby strollers
What was interesting about the project
«No contextual advertising guru will save your business if you work in a falling market. We took up such a project: all macro indicators pointed to the fact that the conversion rate decreased twofold and the market sank by 70%. Let us tell you how we tracked the market decline, what growth points were found, and what came of it in this new case.»
What was interesting about the project:
Advertising budget for a month
Clicks
Leads
«I came to 1jam.ru agency with the problem of high cost per lead and incorrect analytics, which we could not use to compare effectiveness of advertising channels with their expenses. The agency's experts developed a custom model to match conversion to channels, implemented electronic commerce, found problems in Google Analytics measurements and fixed them. What was exciting is that we got a matrix of our current and potential market reach with breakdown by car brand and spare part category, from which we drew a conclusion that we need to expand. Now we are systematically expanding the market reach and reducing the cost per lead. Contextual advertising brings a revenue of 400-600 thousand rubles per month»
After you leave a request: interview ~15 minutes → guest audit access ~15 minutes → audit within 2-4 days → proposal approval → first iteration start. In our experience, it is realistic to get the process rolling in 2-3 days.
Project manager
