Modelplace

Company goals  and  overview of the result

Initially, the task was to test the audience's interest in the product in the U.S. market. Google contextual advertising was chosen as the fastest and most accessible tool for testing such hypotheses. 
 In order for the results of hypothesis testing to be as relevant as possible,
it was necessary to set up an analytics system and build the right user-flow.

Goal: to check the demand for the product in the U.S.

What we are to do for the goal

• Project planning and main strategy formation
• Implementation of analytics of Google, Facebook Pixel, Linkedin
• The website’s integration set up with Notion (CRM), MailChimp, Calendly
• Creating and managing ad campaigns in Google Ads
• Results analysis and Google ads budget optimization

Delivery package

Stage 1: Strategies

We conducted an initial communication with the company's decision-makers, defined the project’s milestones, forecasted the impact and defined  the implementation terms. Then we gathered the necessary materials  for the launch of the advertising company, identified the target audience,
their "pains" and "benefits". Formulated an offer for the end client.

Stage 2: Implementation of analytics systems

As a result we do audits of all the existing analytics systems,  write a Terms of Reference to implement Google Analytics, Facebook Pixel  and LinkedIn analytics systems and run tests to make regulations to the scripts and UTM-tags.

Stage 3: Website integrations

Task: we need to create a minimal viable system for receiving
and initial processing of an application for a startup.  
Suggested scenario for the system:


1. A user fills out a form on the website
2. The information from the request is sent to Notion as a "New lead" with
   1. the request type
   2. the user's email, and
   3. UTM tags
3. The information from Notion is sent to MailChimp with the distribution of users into groups based on the type of request
4. A welcome-email based on the request type is sent through Mailchimp Customer Journey
5. After the user fills out the request on the website, a pop-up window with the option to book a time to meet in Calendly is displayed
6. If the user books a time for an appointment, change in its status to "First contact" should be made.

Solution: The backend has its own API, so it was immediately decided to use Make’s webhook functionality, which is the easiest and most stable option.

We chose Slack as the error reporting system because the team uses
it for duplicating requests from lead forms among other things.

Step by step (the steps correspond to the items from the integration scheme):

1. API module fetches data from the lead form
2. API module sends POST request with received data to Make’s webhook
3. Webhook sends the data to Notion API
   1. If an error occurs at step 3, the information about the data transfer is sent to Slack with error type and description
4. Notion API distributes received information into specified fields in a required workspace
5. Webhook sends received information to Email Sending Service (ESS) API
   1. If an error occurs at step 5, the information about data transfer is sent to Slack with the error type and description
6. ESS API distributes the received information to the specified fields of the required audience
7. Make receives the information about the booking after the user books the time
8. Make sends the information about time reservation to Notion
9. If the user with that email is found in the Notion database, booking time information is added to the user's card
   1. If an error occurs during data transfer, the information about the error is sent to Slack. (this functionality was implemented after the integration scheme was drawn, so it is not there)
10. If the lead was found and the booking time was successfully added to their card, changes in the status of the lead are made from "New lead" to "First contact".

Stage 4: Creating and managing advertising campaigns

We developed a promotional campaign in Google Ads, gathered the semantic core and cleaned it from junk queries. Then we launched the ad campaigns
for the search engine and redistributed the budget. Following the writing  of a ToR for drawing banners and finally we tracked first results and provided
a report with all the information needed for transparency purposes
 to the customer.

Stage 5: Results analysis and optimization