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Prospect Identification – Marketing Automation
Client
This solution was developed for our own internal use to help us in developing market intelligence, leading to demand generation tools.
Objective
One of our primary sources for identifying prospects is job sites. Every day, we identify potential customers from professional job portals by matching their job postings and our service offerings. The data thus sourced by marketing professionals is then validated against certain metrics that we internally use to qualify our prospects. The end-to-end process required dedicated resources and hence was both time and effort consuming. Hence the objective was to automate the process completely by leveraging Robotic Process Automation.
Challenges
Though the process seems straight forward, at every step, intelligence needs to be applied. For instance, the search results need to be segregated based on relevance. Then each result had to be validated by extracting information from other websites such as LinkedIn, Zoominfo, Crunch base, the company’s website and using those details to ascertain prospect qualification. Hence beyond simple rule-based processing, the solution required intelligent cognitive automation.
Solution
At Congruent, we decided to build a complete RPA solution using UiPath. We designed
and developed several bots for Web browser automation, Automated data extraction,
Report generation & distribution and email automation. Finally, the entire process was
automated as described below:
1. RPA bot will automatically open a browser and log in to the concern job portals.
2. Next, it will start searching for the jobs using the “keywords” we mapped.
3. The bot, then, narrow downs the search results using filters like Posted date, Country,
Designation, Key Skills etc.
4. Once the search is done, the bot will automatically extract the data and saves into an
excel sheet.
5. Next, the bot will initiate the process of removing duplicate data.
6. Later, the bot opens the validation portals and validates the sourced data with given
metrics.
7. Finally, the bot will send an email confirmation to the users to inform the status of the
process.
Cognitive intelligence was built into the solution using UiPath’s NLP capabilities and by
invoking ML models written in Python from UiPath.
Benefits
With help of automation, we were able to realize 60% increase in productivity compared to the manual process and were able to redeploy our workforce to other core activities. Further, because the prospects were better qualified, our conversion rates also increased by 50%.
Technology Used
UiPath, Python
