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KNOW YOUR IDEAL

CUSTOMER

PROJECT: 
Machine Learning Based Customer Profiling
nodejs, expressjs, angularjs, Solr
NLP, Text mining, Python, Tensorflow
CDP - RiLey
Google Cloud Platform
TECHNOLOGY: 
RESULT:    

66% increase in conversions 

3X increase in marketing campaign efficiency

Background
Our client is a global leader in next-generation cyber security solutions. They provide security products and solutions to protect small, medium, and enterprise businesses from advanced threats, malware, and other cyber-attacks.  
Problem statement 

Marketing wanted to create a lead database based on such as company readiness, intent to buy, role-based personas that are not possible using standard firmographic filters: 

  • Is an account ready for a specific product or service? 

  • Who are all the actual decision makers and influencers and how do they stack up? 

  • How does one best curate the required pipeline of leads from this sea of prospects? 

Problem identification  

aimify security and marketing experts studied the intricacies of the various cyber security offerings and the associated decision-making tree. In addition, we interviewed marketers and CRM opportunity reports to understand how the customer profile had changed over the various offerings and got anecdotal feedback as what would make a prospect click. Some of our findings: ​

  • Having appropriate technical know-how and having the resources to drive the change were found to be as important, if not more important than IT Spend.  

  • Off-the-shelf prospect databases provide the same prospects to all,  meaning that the prospects are often getting hit by marketers and inside sales from across the board. 

  • SDR interviews showed that sales reps often used social media sites such as LinkedIn and Twitter zone into a prospect

  • In addition, our study showed that just having a champion internally - someone who has experience of driving such a solution/ implementation meant a higher likelihood of success 

Solution

  • Identified a secret sauce of about 10k+ key markers to classify a prospect's relevance

  • Machine learning based lead score

  • Access to the prospects' various specialties and role based functions

  • The solution included 

  1. Natural language processing

  2. Text mining 

  3. Big data & data warehousing 

  4. Machine learning based ICP creation 

Technologies used 

  • nodejs, expressjs 

  • angularjs 

  • Python, Tensorflow, R 

  • Riak, Solr 

  • Google Cloud Platform 

Outcome

  • 66% increase in conversions 

  • 3X increase in marketing campaign efficiency 

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