Lead Generation Case Study: How to generate 40 SQLs in just 1 month in the Banking Industry.

Case study Lead generation / demand generation B2B 7 min read

This case study for our LinkedIn Lead Generation system perfectly depicts how a combination of an innovative FinTech solution and a proper outreach strategy can generate impressive results.


Aspire is a Singapore-based company that provides an innovative banking solution, allowing businesses to solve short-term cashflow gaps. Here’s how TechCrunch described Aspire in 2019:

Aspire operates a neo-banking platform to help small and medium-sized enterprises (SMEs) quickly and easily secure working capital of up to about $70,000. AspireAccount, the startup’s flagship product, provides merchants and startups with instant credit limit for daily business expenses, as well as a business-to-business acceptance and other tools to help them manage their cash flow. - TechCrunch

Unlike other solutions in the niche, Aspire offers Line of Credit model instead of conventional Term Loan, allowing businesses to receive a credit up to SGD $150,000 (Singaporean dollars) for up to 6 months.

Aspire’s solution is unique in that their repayment model only requires users to pay for credit they actually use which gives them the ability for early repayment with no additional penalties.


It would seem that with such a beneficial product, lead generation would be a piece of cake. But there is no lead generation campaign without a challenge, and this one is no exception.


To convert a lead in this niche, it was crucial to reach the right person within the target company. This person should be both a decision-maker and someone who has sufficient financial background to evaluate the benefits Aspire’s service delivers.

To make it even more interesting, it’s important to mention that Aspire’s marketing strategy is focused on growth within Southeast Asian markets, making the targeting requirements even more narrow. Overall, there are about 78 million of small enterprises (their target audience or TA) in our target region.

To make it even more challenging, Aspire defined 4 main TA features that would qualify prospects:

  • The prospects should hold a CEO position, or be the company’s Founder or Director
  • Their company has to be either Pte Ltd, LLP, or LLC
  • Prospects have to be in Singaporean
  • The companies’ bank account has to be active for at least 6 months

However, finding these exact prospects was the main challenge. First, these companies were not well presented on LinkedIn. And second, LinkedIn’s Sales Navigator search filters allows you to configure only 2 of the above requirements, don’t they?


The inbox of the average business owner is an extremely crowded place. It is mostly filled with spammy messages from bots or companies, trying to constantly shove their sales offer in the account owner’s face.

Even having the best offer or highest discount might not work to grab the prospect’s attention because of this new form of ‘ad blindness’. People will just ignore your message anytime they feel you are trying to sell something right away.


1. Target Audience Research

To make sure we connect with the right decision-makers at the right companies, during our lead generation campaign we came up with a system that still used LinkedIn Search mechanics to filter prospects. In particular, we leveraged:

  • Location filters
  • Industry search
  • Title search
  • Company size filters
  • Keyword boolean search.

You can learn more about LinkedIn’s Filter mechanics here.

The exact search configurations we used are as follows:

  • Industries:
  1. Marketing and Advertising
  2. Computer Software, Information Technology and Services, Internet
  3. Banking, Financial Services, Insurance, Management Consulting
  4. Education Management, Higher Education, Primary/Secondary Education, Professional Training & Coaching
  • Company headcount: 1 - 50
  • GEO: Singapore
  • Titles: CEO, Director, Founder, Co-Founder, Owner, Co-Owner

Using this configuration, we were able to search find several thousands of prospects, mostly in Marketing and IT segments. These segments helped us create targeted aggregate lists to make sure our messaging outreach could be adapted to the respective industry.

Our strategy was to let our messaging do the heavy lifting in terms of qualification of an SQL while still generating awareness in a broader target audience.

You can learn more about LinkedIn Lists mechanics here.

2. Message Script Creation

We always recommend choosing a personalized and sophisticated outreach strategy whose communication considers recipients’ personal circumstances and that establishes a dialogue before presenting an offer, making a conversion more likely.

As LinkedIn Lead Generation is a top-funnel activity, it was crucial for us to establish a personal dialogue with every prospect to proceed with further nurturing and conversions.

For that, we used a 4-level messaging sequence, consisting of:

  • Direct and honest connection request. We would introduce the professional, sharing some facts about Aspire’s previous success, as well as the goal to penetrate a particular market.
  • Qualification message, that included statistical data that displayed Aspire’s recent growth. This information was followed by introduction of the core service and finished with a qualification question to determine whether prospect does have the pain points we’re looking for.
  • Offer message. This one was created with 3 variations, adapted to the type of reply we would receive after qualification message. A positive scenario would include an offer to book a call, while negative and neutral would share a TechCrunch article featuring Aspire to gain extra credibility.
  • Follow-up message with CTA. Also divided into 3 options, where a neutral and positive response would request the lead to book a call, while a negative response would direct traffic to Aspire’s blog so prospects can learn more about potential benefits.

It’s important to mention that the messaging sequence was adapted every time we changed the TA segment we reached out to, to make sure we addressed the right pain points.

3. Outreach

In just a month, we were able to prequalify profiles amongst several thousands to send almost 2500 connection requests which converted into over 500 pre-qualified connections. More than 20% of connections replied to our messages, while almost 50% of those who replied converted into hot SQLs. Considering that an average benchmark of connection and reply rates is below 15% for FinTech, Aspire’s projects has shown significant growth (below graph).

13 prospects booked a call right away, with no need for additional nurturing.

Here’s a more detailed breakdown of the performance of this lead generation campaign during the first month.


To provide you with more details of the results, we’ve added some graphs that represent the main metrics we use to measure the efficiency of our campaigns. This is a breakdown of the first month of our campaign with Aspire.

The first graph represents the number of Prospects, generated by our campaign. We classify a contact as a prospect when they accept our invite and then read the message. On this graph, such contacts are marked as “Con. received”.

The next level is Engaged Leads (Total Replies). These are the people who have responded to our messages.

The ratio between the number of Sent Requests and the number of Prospects is called Acceptance Rate.

The ratio between Prospects and Engaged Leads is called Reply Rate.

For Aspire, our acceptance and reply rates were almost always similar rates which shows that our manual pre-qualification of contacts, our invite message and first message were highly efficient.

The Interested Leads are people who showed interest in the client’s services. We use it as our ultimate measure of success, since these SQLs are transferred to the sales team to then go through the sales process. This metric is received by classifying the replies’ temperature and filtering all the Positive replies.

It’s crucial to understand that “Negative” and “Neutral” replies doesn’t mean that the conversion is not possible and that the prospect is wasted. In fact, coping with “negative” replies properly can also generate conversions.

Neutral replies signify leads that are Progressing which means that conversations have been opened and they are now engaged with the sales team to respond to questions, concerns or to be given more information.


This LinkedIn lead generation campaign is a great example of how combining well throughout targeting, our work in pre-qualification, and messaging strategy generated a consistent flow of hot leads for Aspire throughout the first month of this campaign.

Here is a summarized breakdown of results in just one month of our LinkedIn Lead Generation Campaign:

Invitation Requests Sent: 2276
New Connections: 534
Replied: 131
Calls: 13
Acceptance Rate: 23.5 % (Added/Accepted)
Reply Rate: 24.5 %

This campaign is still running. We will update this case study as the results are delivered.

We overcame the challenges of finding a needle in a haystack of target audiences and nurtured them successfully with a personalized messaging and outreach strategy. This is a direct application of what we call Human Learning. AI and automation still have a long way to match our method at Respect.Studio.

Feel free to find other Case Studies here or contact us to find out if your company can benefit from our LinkedIn Lead Generation system.

B2Bmarketing lead generation B2B