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One of the problems that I was trying to solve for a SaaS startup over the last couple of days was the management of outbound marketing, in the presence of inbound, referral, and other acquisition channels, with an ever-growing team of marketers.
As we rolled out campaigns one after another, our team size kept increasing, and suddenly we were sharing data across multiple users, in multiple spreadsheets, across different platforms. Lack of integration and automation along with large amounts of data, with varied structure, added to the already worries of an already stressed marketing team. I thought of developing a custom app to de-duplicate, integrate, and automate, but given we had so little time and resources, I stuck to VLOOKUP, SEARCH & FILTER in sheets.
All of this kept piling up on top of the base problem - Marketing is omnichannel, data-heavy, volatile, and constantly in-action. The accounts you target through outbound activities can discover your product through a different touchpoint, and unless your system is fairly sophisticated, you’ll end up sending a relatively colder magnet/message to a lead, who is way down your funnel already. Outbound marketing is intrusive and no matter how much you attempt to make it not that way, there is always a fair chance of the campaigns hurting you back.
"If only we had a single source of truth, we would be able to identify, segment, and target leads correctly."There was one source of truth for all incoming leads (thank you CRMs!), which I can easily integrate using APIs. So, I started focusing on consolidating Outbound Marketing.I picked up Amazon Honeycode on a Sunday afternoon, and was able to build the tables, automation, ROWFILTERs, calculations and the app, all within 2 hours.
The UI felt quite comfortable, with three basic features - Tables (to store your data), Builder (to develop your app) and Automations (to automate data transformation using workflows).
1. Table1 - This table would serve as the master database of all leads. All properties related to leads, prospecting, qualification, ownership etc. went here.
2. Table2 - This table contained all the team members involved in running outbound marketing. All leads were assigned to team members, who were the owners of them.
3. Table3 - This table had lead stages such as New, Contacted, Registered etc., along with disqualification reasons - Junk lead, Unable to reach, Not interested, Not PMF.
4. Table4 - This table maintained all the sources such as lead lists and campaigns. As we roll out campaigns, we would append the sources and campaigns.
5. Table5 - This table contained all company-level data. Every lead from Table1 is mapped with a company, present in this table.
1. Automation1 - This automation updated default and initial values of properties such as created_by, created_at, sequence_status. Upon creation of a row, these properties would be updated automatically.
2. Automation3 - This automation correlated lead stages with sequence status. For example - if a lead was marked as unqualified, it’d update the sequence_status property to pause.
Finally, I was able to build a custom app, which was fairly easy to create, with the drag and drop UI. I added two screens to it - List Screen and Details Screen. Team members could view all the leads in the list screen, filter the list by owner, company etc. and edit the lead stage from the details list.
Given the app worked on both mobile and web, it streamlined the entire flow of identifying, segmenting, prospecting and maintaining an up to date database, no matter how collaborative the campaigns are.
P.S. - I am running , with the aim of enabling growth of SaaS startups with engineering tools, frameworks, processes etc., (tested and evolved by working with at least half a dozen tech startups).
If you want to connect and discuss more, I am at [email protected]