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Influencer Marketing Software from Scratch

Custom influencer marketing analytics platform with 91% accuracy of influencer behavior prediction.

influencer marketing software
Key Details

Custom influencer marketing analytics platform with 91% accuracy of influencer behavior prediction.

  • Challenge
    Develop a custom analytics-based influencer marketing platform
  • Solution
    PA and NLP models for influencer analytics
  • Technologies and tools
    Machine Learning, Predictive Analytics, NLP;
    backend development – .NET
    frontend development – Angular


The client is a digital marketing agency based in Cyprus. They are experienced in lead generation and organic reach. Founded in 2002 and having over 200 employees, they offer their clients ways to boost their brand efficiency and relevance on the market. The agency connects mid-market-level brands and influencers for marketing needs.

The influencer marketing analytics software for B2B available on the market didn’t fit the client, that’s why they went for custom software development. The client needed a reliable vendor with expertise in machine learning. They decided to develop influencer marketing software from scratch. To tailor to the requirements, the platform must be predictive analytics and NLP-based.

Challenge: develop a custom analytics-based influencer marketing platform

We were challenged to develop a swift influencer marketing analytics software from scratch. The client had nothing but an idea. So, we started to develop a brand new platform – with both backend and frontend, plus integrate predictive analytics and natural language processing into the platform.

Solution: PA and NLP models for influencer analytics

The client has decided to collaborate with the InData Labs team as our company has got impressive expertise in AI, data science, and natural language processing.

We also have hands-on experience in developing and improving similar influencer marketing software for agencies.

Our tech team drew upon different resources to meet the client’s needs. To do that, we had to stick to that plan:

Project development stages:


  1. Gathering requirements (discussing project vision with the client, establishing project goals, prioritizing features, finalizing the requirements)
  2. Defining the project scope (identifying features, confirming achievable features, identifying constraints and acceptance terms)
  3. Developing the platform (building architecture, developing backend and frontend, integrating ML models into the platform)
  4. Stabilization (double-checking everything)
  5. Delivering the project to the customer (presenting the results to the client’s management board)
  6. Support (on-demand consulting)

The client needed to build a platform valuable for both brands and influencers. Influencers could monitor follower activity and have access to audience insights. Both metrics are vital for strengthening online presence.

content and audience analytics summary

Brands, in turn, could set up campaigns and later track its performance (new followers, views, likes, comments, mentions, etc).

When the backend and frontend part was finished, we moved on to implementing ML and PA models into the platform (they were also developed on demand). ML models allowed for effective campaign performance analytics and influencer behavior prediction. NLP models were used for sentiment analysis. They help interpret social media feedback with accuracy up to 92% and adjust marketing strategy.

Influencer Marketing Software

Result: brand new platform to improve marketing efforts

As a result of the collaboration with us, the client got a robust B2B influencer marketing software that connects brands and influencers for marketing purposes.

The platform developed by our team has advanced the client’s business.

These are the key benefits of the platform:

  • solid software catered to the client’s specific needs
  • real-time analytics on influencers (performance, reachability, target audience, engagement rates, location,
  • nationality, language, age, gender, interests, etc.)
  • competitor brand analysis
  • on-demand campaign monitoring and analysis
  • fast influencer/agency search in plenty of social media channels
  • relevant influencer offerings
  • automatic reports generation

Benefits in numbers:

  • 91% – influencer behavior prediction
  • 97% – fake influencer detection
  • 92% – sentiment analysis accuracy
  • 20% – reduced marketing costs

Need a Custom Predictive Analytics Platform? Let’s Talk.

  • Marketing & Advertising
  • Machine Learning
  • Predictive Analytics

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