Witbee & Orange success story part two

Orange success story

In 2017, Orange Polska, in cooperation with Witbee, decided to introduce an analytical culture to its organization. The cooperation translated into an increase in the number of contacts with Orange Polska by as much as 86%. - case study part one
Is it possible to achieve even more after such spectacular increases? Definitely yes. Here's what we managed to improve.

Goals

To introduce and adapt advanced attribution models to telecom products and processes
Increase sales in the acquisition segment in the key marketing channel - i.e. the search engine - excluding keywords containing the phrase "Orange"

Results

Increase in the number of contacts made by customers by 55%
Increase in sales of the product "optical fiber" by 53%
41% increase in sales of all internet products in acquisition
Further reduction of marketing expenses in the Google Paid channel, by 42% per annum
Create an environment and propose new possibilities of analysis using attribution models.

Strategy

Implementation

Results

Challenges

How has it come to this? Our first step was to define a new strategy

Our main goal was to increase acquisitions, i.e. attract new customers. Data integration - described in the first part of the case study - allowed us to quickly complete this task.

We used the Cloud technology and the module of the Witcloud Google Ads Export tool. It is used to send sales data directly to the Google Ads system. We also used this module to send conversions in various attribution models, directly to Google Ads accounts. Attribution was performed on sales data provided from various sales processes and systems of Orange Polska.

Thanks to this, we obtained the following benefits:

The analysis process at the report level has been shortened for faster analysis directly in the advertising system.
All keywords (search terms by users) that contained the phrase "Orange" have been eliminated. The phrase "Orange" collects a lot of traffic, generated as a result of TV, radio and press campaigns. However, we wanted to distinguish between campaigns that attract acquisitions - and not support traffic generated through other marketing channels.
The budget was transferred to the appropriate part of the acquisition campaigns.
General words that are effective in canvassing sales were selected.
Data attribution was used to locate acquisition campaigns in the advertising system.
Attribution was used to locate keywords effective in terms of acquisition.

In the next step, we only had to carefully separate the inquiries directly related to the phrase "Orange" from the acquisition campaigns and focus on the latter. Sending sales data to the advertising system gives you many possibilities - let's move on to the strategy implementation methodology to get to know them better.

Implementation of strategy

When we started working with Orange in 2017, we managed to successfully implement data processing and reporting processes provided by Google Cloud and Witcloud technology. This time, however, we went a step further. In the integration, we have added another process - sending BigQuery data to Google Ads.

Thanks to the new process (Witcloud -> Google Ads), it has become quite simple to separate the strength of the Orange brand, select the appropriate terms in terms of sales and translate the strategy into new acquisition campaigns.

There is a report of user searches in the Google system. After integration, this type of report can be combined with sales data. Thanks to this, we know which keywords entered by users most often end up with the purchase of a specific service.

Such knowledge is of course a huge treasure. It allows you to make accurate marketing decisions. Creating accurate and highly effective campaigns and full optimization of activities. Data analysis is convenient and simple, and marketing campaigns on sales data are performed directly in the Google Ads system. Or fast and very specific.

On the basis of our implementation, we managed to build a new campaign structure and made further optimizations.

„Our cooperation has enabled us to build an analytical culture and make data-driven decision. This has been proven by increasing sales and reducing cost in marketing activities”.

Adam Skręt | Digital & Performance Director, Orange Polska

Results over 4 years - 4 years of cooperation

In the first part of the case study, we used integration, i.e. combining offline data with online data in analysis and reporting. As a result, we managed to achieve a significant increase in contacts with the Orange brand. Specifically, it was an increase of as much as 86%.

In this part of our activities, we used data attribution to identify and support our acquisition activities. And also to export sales data to the Google Ads system and to further determine which keywords (without the phrase "Orange") sell the internet.

As a result, the activities undertaken in 2020 resulted in an increase in final internet sales by as much as 53% and a reduction in advertising expenditure by as much as 42% per year! (Note that we're referring to the period of 2018, which is the previous success).

The Challenges ahead

Despite the double business success, the list of challenges and the possibility of further optimization remains quite long. Orange products have different sales processes - the customer can buy an internet offer, telephone subscription, etc. With such a large number of different products, it gives a lot of room for action. Additionally, the Orange organization works and changes dynamically, creating new processes or working on improving the existing ones. Maintaining integration and responding to the dynamics of Orange changes, for which the Witcloud platform is responsible, is a big challenge.

Let's also not forget that the Orange brand has both simple processes (e.g. contact leaving and contacting the hotline) as well as more complex ones (e-commerce store, where the user performs more events on the website). It also broadens the potential activities.

Challenge I: Combining processes and bidding in Google Ads

Combining the processes into a sum and creating one calculated field from them and the use of Google Ads bidding algorithms would be another milestone on the way to better optimization. Human resources are not able to respond as often and precisely as is the case with Google's machine engine. So here we would get a significant improvement.

Challenge II: Using predictions in Google Ads bidding

The essence of this challenge is the use of advanced elements of Cloud technology and cooperation with the Witcloud tool. If properly configured, it could allow the use of Google Cloud ML machine modules to predict whether a specific service will be purchased.

The system could make a prediction concerning e.g. Internet service purchase within the next 7 days. Is such a thing even possible? Well, that question should be asked using the word "when" rather than "if". At least in the context of WitBee.

We will probably present the effects of implementing both challenges in the third and last part of this case study.

Rate article

Image: Freepik

How to increase Internet final sales by 53%