REACT TO INBOUND LEADS

IN REAL-TIME

PROJECT: 

Automated Data Enrichment & Notification of Inbound Leads

Quickwork 

Python, Tensorflow

Salesforce.com 

Google analytics, tag manager 

Clearbit 

SMS via Twilio 

TECHNOLOGY: 
RESULT:    

167% increase in conversions from inbound leads

Background
Our client is professional services company providing services in technology consulting, product development and SAP implementation services. They were in growth mode with additional funding acquired from their investors. 
Problem statement 

Our client had a successful client base that were acquired over a long period of time primarily through traditional marketing and trust-based relationships. Now that they were in growth mode with additional funding, they were shifting heavily to inbound strategies. They had made significant investments in ad campaigns, SEO and social media campaigns.

However, they struggled to get the results they had expected from the inbound campaigns. Management struggled to provide a business case for additional investment to sales & marketing campaigns because the sub-standard outcomes from their inbound campaigns. Investors were getting impatient not seeing an increase in the quarterly revenues as forecasted by the managers. 

Problem identification  
  • Technology stack was not geared to handle the immediacy and volume of inbound leads

  • Large volume of inbound leads were getting lost in time 

  • SDRs were often focusing on unqualified leads. Better suited leads were slipping through the cracks because of lack of data enrichment and lead qualification 

  • Lead scoring was largely intuitive 

Solution
  • Configuring UTM codes for the various marketing campaigns 

  • Optimizing Google analytics and tag manager to differentiate between customer audiences and marketing campaigns 

  • Using quickwork to create an automated workflow that included: 

    1. Automated data enrichment using Clearbit to obtain additional information about the prospects 

    2. Data standardization 

    3. Python and NLP based lead scoring 

    4. Lead filtering and routing to appropriate SDR in salesforce.com 

    5. SMS to SDR so that they would react in real-time 

  • Data analytics and dashboards for reviewing time to response, lead quality 

Technologies used 
  • Quickwork 

  • Python, Tensorflow 

Integrations 
  • Salesforce.com 

  • Google analytics, tag manager 

  • Clearbit 

  • SMS via Twilio 

© 2020 by Aimify

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