



Client: OASIS Optimisation
Contact Person: Pierre Coetzee, Consulting Partner

OASIS Optimisation is a South Africa-based research and analytics consultancy that helps organizations make better decisions through data. Their work sits at the intersection of strategy, consumer insight, and quantitative research, with a strong focus on hospitality, tourism, and destination intelligence.
When clients need to understand what people actually think and feel, OASIS builds the frameworks to find out.
Pierre Coetzee, Consulting Partner at OASIS, and his team were approached by a tourism ministry with an ambitious request: understand the full visitor journey, starting with accommodation.
The goal was to analyze how travelers were experiencing hotels and resorts across the country, and then benchmark that against other destinations.
The project needed scale. We’re talking about hundreds of properties, thousands of reviews, multiple languages, and data that had to be aggregated at a regional level to be meaningful.
Without turning to a review monitoring tool, OASIS had two realistic options, but neither was the best fit:
“You’d have to put a lot more time and effort into making sure it collects the right data.” — Pierre Coetzee, Consulting Partner at OASIS Optimisation
“It’s definitely a lot more time-consuming and expensive. You’d have to design your own measurement instrument, then collect the data through a primary research methodology, and then analyze the data. It’s definitely a lot more expensive to go that route.” — Pierre Coetzee, Consulting Partner at OASIS Optimisation
What OASIS needed was a way to get reliable, structured review data at scale, quickly, and without the overhead of building or fielding their own research from scratch.
Two things mattered most on this OASIS project:
In addition to this project, Pierre and his team wanted to build a methodology that could serve their future clients, so the team won’t have to reinvent the wheel every time they are tasked with similar projects.
OASIS evaluated their options and chose Mentionlytics as the most practical path forward for this kind of ratings and review extraction at scale.
Unlike general-purpose social listening tools, Mentionlytics offered something the alternatives couldn’t: access to structured review data on accommodations across the country they targeted, delivered quickly, without requiring OASIS to build and maintain their own data pipeline.
The fit became clear almost immediately once they were set up. The keyword logic allowed them to pull data at the level of granularity they needed, and the review-level exports gave them exactly the raw material required to run their own modeling on top.
The first phase of the project was all about getting the right data, fast. OASIS used Mentionlytics to extract reviews about accommodations in the target country, with each record including:
Keywords were configured to allow aggregation at the regional level, which was the primary unit of analysis for this project. That meant OASIS could roll up the data across an entire region or drill down to individual hotel performance, should the client need it.
From setup to having clean, usable data in hand: less than one week!
In the screenshot below, you may see the total volume of reviews the OASIS team was able to collect in less than a week (historical and latest data combined).

That timeline alone changed the economics of the project. No fieldwork, no custom infrastructure, no waiting.
Before OASIS moved the data into their own modeling environment, they used the Mentionlytics platform to do a first-pass sanity check. They explored keyword combinations, validated that the data being pulled matched the brief, and got an early feel for the themes emerging in the reviews.
By exploring different keyword combinations and zooming out of review platforms only, Mentionlytics provided OASIS with rich mention data from social media users who shared their experiences on YouTube, Instagram, X (Twitter), and other popular social channels.

This step was of utmost importance because catching keyword gaps or data quality issues before running topic models saves weeks of rework downstream.
The total number of reviews (including social media mentions) that OASIS gathered through Mentionlytics was more than 160K.
Especially, those reviews posted on social media wouldn’t be accessible to OASIS through custom web scrapers or other traditional research methods.

Once the raw data was validated, OASIS imported it into their internal modeling system and got to work.
Every review was classified into specific topics. Ratings and sentiment were then analyzed against those topics to identify where guests were satisfied, where they were frustrated, and how the target country compared to benchmark destinations.
Total time for modeling, translation, and dashboard creation: approximately 4 weeks.
Total project time from setup to first deliverable: 5 weeks.
The tourism ministry received a decision-ready view of how visitors experienced accommodation across the country, broken down by region and topic, with sentiment benchmarked against competitor destinations.
But the outcome that OASIS values most is what the project left behind internally.
They now have a proven, repeatable workflow for extracting and modeling ratings and review data at scale. The models are built. The scripts are ready. Future projects in different industries or for different clients don’t start from square one; they start from a working playbook.
One practical improvement they are already planning for multilingual projects: requesting both the original language and the translated version from Mentionlytics upfront, rather than handling translation downstream.
A small process change that will save time on every future project that involves non-English reviews.
If you are considering Mentionlytics for large-scale data projects, Pierre’s takeaway is simple: the platform is the fastest way to get structured review data at scale without the cost and lengthy process of primary research.

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