You cannot solely rely on organic marketing when it comes to running a startup, especially when you are just starting out. A little kickstart can help a lot to bring in those first few leads aka revenue. And paid advertising can easily make it happen.

In this post, we’ll share our insights and 5 key areas to consider when strategizing for your paid advertising:

  1. When to consider paid ads
  2. Which platform and who to target
  3. How much to budget for
  4. What metrics to track
  5. How to optimize for results

When should you use paid advertising for startup?

Should you start running ads?

Paid ads is a good idea in these two scenarios:

  1. You are early in product building: Your goal is to get early batch of users and test your messaging, targeting etc. At this point, you need to set realistic expectations with your ROAS and CAC.
  2. You’ve found product-market fit and ready to scale: You roughly know what resonates with your audience. At this time, you can start focusing on cost efficiency.

Paid ads can be your powerful growth channel given the right investments.

Pros:

  • It is scalable, unlike other growth channels such as Product Hunt, Newsletter.
  • It produces high volumes of data rapidly, helping you learn and iterate faster.

Cons:

  • It takes at least 3 months for campaign to be cost efficient / profitable. Ad platforms need time to learn from your data.
  • You need to allocate substantial resources (effort, time, money) to launch great campaigns.

A common pitfall for startups venturing into their first paid ad campaigns is losing momentum after a few weeks, resulting in wasted funds and missed learning opportunities.

Hence, before jumping into paid ads, ask yourself:

  • Have you exhausted other cheaper growth channels that could help you improve your website conversion rates, messaging and targeting?
  • Can you commit to 1 to 3 months of resources and spend?

Which platform and who to target?

Choosing which type of paid ads and platform for your digital ads ultimately depends on where your users are. Think about your target audience’s demographics, interests, and behaviours, which platform suit their profiles?

The common types of paid ads include:

  • Search engine advertising (Paid Search): Google ads, Microsoft or Bing ads
  • Social media advertising (Paid Social): Facebook ads, LinkedIn ads, TikTok ads
  • Display advertising
  • Video advertising
  • Native advertising

What is Paid Search?

Paid search advertising is a type of digital marketing strategy where brands place their ads in the search engine result pages (SERP) of Google, Bing, and other search engines.

It’s great for driving traffic and getting high-quality leads, and eventually customers.

What is Paid Social?

Paid social advertising is a method of advertising your product or service on social media to a targeted audience.

It’s great for building brand awareness and retargeting specific audience.

Comparison between Paid Search and Paid Social

Ad Platform Best for Tips

Paid Search

(Google, Bing)

Targeting audience actively searching for solutions (high conversion intent)

Gauge search volume by conducting keyword analysis using Google's Keyword Planner

  • If low, consider other channels like Paid Social, SEO, or Events; your target audience may not be aware of the solution
  • If high, adjust budget allocation based on seasonal search trennds

Paid Social

(Meta, LinkedIn, TikTok, X)

Building brand awareness.

Retargeting campaigns. Don't miss out especially if:

  • You have a specific audience in mind to retarget
  • Your product has a long purchase cycle, thus requiring a full-funnel marketing approach

Develop high-quality assets (visuals, ad copies) relevant to your target audience.

Regularly refresh ad assets to prevent ad fatigue, especially for smaller audience sizes.

Tip: Don’t just spray-and-pray. Do a competitive analysis to find out where and who your competitors are targeting. Learn about their Ideal Customer Profile and messaging that resonates.

How to allocate budget for paid ads?

If you’re just starting out, consider allocating an amount that's manageable enough to risk, yet substantial enough to collect meaningful data.

If your budget is too low, it takes longer for the ads platform to optimise your campaigns, thus lower performance and slower learning for you.

If your budget is too high, your ROI will be low as paid ads is subjected to the law of diminishing return.

  • For Paid Search: High budget for product with low search volume means that ads will show for random low intent keywords.
  • For Paid Social: High budget for product with small audience means that ads will either be (1) shown to random people or (2) very frequently to the same group of people, making them desensitised or even have negative sentiment to the brand.

Tip: Try out this template we use to get an estimate of budget, conversions and customer acquisition cost.

How to measure paid ads performance?

You can't improve what you don't measure.

Below a list of digital marketing metrics you should know, sorted by importance in the context of paid advertising.

Tip: Compare your metrics against industry benchmark or other channels.

Metrics Tips

Return on Ad Spend (ROAS)

= Total Revenue / Total Ad Spend

*Revenue could be lifetime value (LTV) for subscription products.

  • At early stages of running ads, your ROAS will be below 1– don't freak out! It takes time.

Cost per Acquisition (CPA)

= Total Ad Spend / Total Conversions

  • Compare CPA or CAC against your average monthly revenue per user to identify your target payback period. Is this within your tolerance?
  • Depending on your business, CPA doesn't always equal to CAC.

Conversion

Campaign success indicator, based on completed desired actions (eg. purchase, signup)

  • Check the quality of conversions and ensure they directly contribute to your business goals.
  • Eg. if your ultimate goal is getting leads, you'd need to measure the number of qualified leads, not just simple form submissions.

Conversion Rate (CVR)

= (Total Conversions / Total Clicks) × 100%

  • Low CVR suggests poor landing page design, content, or traffic quality.
  • High CVR– great job! Now check if CPA is within your desired range. If yes, you can consider scaling your campaigns.

Click-through Rate (CTR)

= (Total Clicks / Total Impressions) × 100%

  • Low CTR may signal poor ad copies, creatives, or targeting.
  • High CTR– great job! Now check if traffic if of high quality. High CTR with low CVR may signal fraudulent clicks.

Cost per Click (CPC)

= Total Ad Spend / Total Clicks

  • Low CPC doesn't always mean good traffic.

Impressions

Indicator of brand awareness, potential reach

  • In the context of SEM, this could be a proxy for search volume.
  • If impression is high but CTR is low, experiment on different copies, creatives; targeting (or keyword selections for SEM).

Click

Shows user interest, potential conversions

If number of clicks is too low, this means other starts are not statistically significant. So be wary of making decisions purely based on data.

How to track your marketing KPIs effectively?

If you have started acquiring customers from multiple sources, it is essential to measure and track various KPIs and break them down by channel. This allows you to understand:

  • Which channel drives the best quality traffic?
  • Which channel is the most cost-effective?
  • Which channel should be scaled?

Building a Minimum Viable Marketing Analytics Stack

Struggling to find answers to the questions above? Setting up a minimum viable marketing analytics stack could help.

If you’re just starting out, the end product can be as simple as having a spreadsheet where you manually update KPIs regularly (weekly/monthly). However, the key is to have reliable sources from which you can obtain each metric value.

At a later stage, you may want to invest time and money to build a data analytics pipeline that provides access to raw data and allows you to create custom dashboards.

The following diagram shows the high-level architecture of a marketing analytics stack:

Flowchart illustrating the architecture for data-driven marketing, showcasing acquisition sources like SEO, paid ads, and organic social media, integrated with website tracking tools, centralized data storage, and data visualization platforms

Essential components

Data sources:

  • Web analytics platforms: Google Analytics (free), Mixpanel, Posthog, Amplitude, Heap.
  • Acquisition channels: Google Ads, Facebook Ads, etc.
  • CRM/Sales app: Hubspot, Shopify, etc.

ETL tools to transfer data from source to destination:

  • No-code ETL platforms like Airbyte or Fivetran.
  • Marketing-specific tools such as Supermetrics or Funnel IO.

Reporting tools:

  • Visualization tools like Google Data Studio, Metabase, or PowerBI.
  • A reliable spreadsheet.

How to optimize ad campaigns?

  • Iterate with A/B tests: Compare different variations of ad copies and creatives to see which perform better for you.
  • Avoid costly paid ads mistakes by analysing competitors’ ads: Which of your competitors’ ads survive the test of time What USPs do they focus on? How much budget and effort have they invested?
  • Leverage on industry trends: Adapt based on seasonal changes, algorithm updates, new creative directions.

FAQ

Is paid search the same as paid social?

Paid search differs from paid social. While paid search targets audiences based on keywords actively being searched for, paid social targets audiences based on interests, behaviors, and demographics.

How do you choose the right paid ads channel?

Define business goal and campaign objective

  • Is it to increase brand awareness, conversion or others?
  • Each channel has its unique proposition and serves different needs

Identify where your target audience hangs out

  • Think about their demographics, interests, and behaviours.
  • Paid ads channels can be broken down into Paid Search and Paid Social.
  • For each channel, gauge the traffic volume and growth potential to help you prioritise which channels to test.
  • Where your competitors are advertising can be a good starting point.
  • We built a tool to collect and analyze your competitors' ads, all in one place. Check out Kaya's Competitor Ad Intelligence tool.

For each channel, calculate CPL. Ideally, you’d want to focus on channels with lower cost with a sizable reach.

  • Account for at least 3 months of budget for the campaign to be cost efficient / profitable. Ad platforms need time to learn from your data.
  • A common beginners pitfall is losing momentum after a few weeks, resulting in wasted funds and missed learning opportunities.
  • Tip: Try out this template we use to get an estimate of budget, conversions and CPL

Experiment and scale

  • Run A/B tests to identify the potential customer segments, messagings and creatives.
  • Analyse lead quality, customer LTV acquired via each channel.
  • Prioritise channels that can scale sustainably. At this point you may also think about hiring a specialised agency or in-house to manage them.

Should a startup hire a marketing agency?

Yes. Marketing agencies allow you to improve your marketing and ad ROI while reducing ad spending. Hiring a marketing agency also frees up more time for you to commit to product development.

How do I find a startup marketing agency for my business?

The first step is to consider your business needs. Then, look for and speak to startup marketing agencies that fit into them. You want an agency that delivers results quickly. For instance, Kaya delivers visible results in 2 weeks.

How do I choose the best marketing agency for my startup?

Identify your business goals, search for startup marketing agencies in your industry and evaluate every potential partner. Review their websites and social media handles to learn about their services, pricing, and past performance. Also, consider your budget and the cultural fit and ensure that these are fully aligned.

Final thoughts

We've just uncovered the 5 key areas to consider when strategizing for your paid advertising.

From when to run paid ads, targeting platform and audience, budgeting, metrics to campaign optimization - the exciting journey has only just begun.

Picture of author Hailey Chong

Hailey Chong

Data Scientist (former), Kaya

Hailey was a Data Scientist at Kaya. She excelled at combining storytelling and data to drive impactful growth. Outside of work, she mentors budding professionals, judges hackathons, and shares her journey on LinkedIn to inspire curiosity and innovation in others.