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ML and NLP Models For Marketing & Advertising

Enhanced consumer behavior prediction up to 89%.

ML & NLP models for marketing and advertising
Key Details

Enhanced consumer behavior prediction up to 89%.

  • Challenge
    Analyze data and discover marketing insights faster
  • Solution
    Machine learning models for marketing & advertising
  • Technologies and tools
    Artificial Intelligence, Machine Learning, Natural Language Processing


The client is a global beauty company with a focus on natural artisanal products. They are popular among clients across the world. The brand has monthly product launches and gets to analyze tons of customer data. So they have trouble gathering, analyzing and gaining insights from the product reviews.

Since the client is a multinational brand, it especially makes it hard for them to do sentiment customer analysis. Today, they do it manually, and it takes up too much time and resources. As a result, they fall down on work and miss out on lots of insights. That’s why their marketing team started to think about adopting AI and machine learning in marketing activities.

The client asked the InData Labs team to help them use the power of AI and machine learning in marketing goals.

Challenge: analyze data and discover marketing insights faster

Our tech team was to address the following challenges:

  1. Automate data collection and analysis
  2. Get quality prediction of customer behavior
  3. Get insights out of customer data to readjust marketing and advertising activities
  4. Apply NLP models for fast and efficient multi-language sentiment analysis
  5. Find beauty influencers to collaborate with

Solution: machine learning models for marketing & advertising

The client has chosen InData Labs for two reasons. First, InData Labs has had broad experience in AI and data science. Specifically, experience in developing machine learning models for marketing initiatives. Second, we have had our proprietary social media analytics tools. Integrating an analytics package is easier and faster than developing a new one from scratch.

During the project planning phase, we gathered all the client’s requirements, estimated time and risks and came up with a set of plans.

Since they wanted to make the most of their data, we decided to integrate our custom AI and ML models into their platform. That was the easiest way to analyze customer behavior and target more defined segments. The narrow segment is easier to do advertising. Machine learning models for marketing, we gave access to, enabled tracking engagement metrics and content performance. Using ML, the client can understand where it’s safe to place ads and where it’s not. It saves the trouble of posting the content on the wrong platforms and at the wrong time.

Our team also helped the client turn customer reviews into insights. We leveraged NLP to help them understand how the audience perceives their brand, how they like their latest release and what they’re posting about it in socials. Sentiment analysis suggested how to reshape the next release and better target audience.

Result: fast data analysis, consumer behavior modelling and prediction

We helped the client uncover the power of machine learning for marketing.

Our solution has significantly benefited the client’s brand and has let it hold the cards on the beauty market.

Benefits in a glimpse:

  • automated data collection and analysis
  • consumer behavior prediction (accuracy up to 89%)
  • brand health tracking
  • sentiment analysis in multiple languages (accuracy up to 93%)
  • real-time beauty influencer analytics – influencer performance, fake influencer detection, reachability and
  • engagement rate tracking, audience insights)
  • audience insights to boost contextual relevance and tune the right type of adds
  • 35 beauty influencers found via our platform
  • 8.3M impressions achieved through Instagram creator collaborations in 3 months
  • real-time brand campaign monitoring
  • machine learning models used for better online advertising

Empower Your Business with Machine Learning-Based Models

  • Advertising
  • Natural Language Processing
  • Predictive Analytics

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