60%

Boosted digital KPIs seen within 2 weeks or faster [see case study]

The results speak for themselves (e.g. massive improvement in an already well-run account). Sadly, I’ve directly seen the shortcomings of other service providers that pay ‘lip-service’ to ROI but lack the ability to fully deliver.

I’ve never seen a digital ad account I couldn’t improve significantly, because I’ve developed unique IP in combining 3 strengths:

• A decade of digital experience: I’ve built countless solutions and know what works and doesn’t

• General strategy consulting work and MBA education: The macro viewpoint and problem-solving skills outside of marketing, for that extra edge

• The ‘quant’ part: doing the work of deep data analysis and exact calculations. See video case studies where I find growth opportunities and cost savings that are overlooked by others

I’m happy to jump on a call to discuss the benefits of my process and the results (check out this case study). Also, I’ve successfully executed full service across all digital ad activity, even across multiple business lines (B2B and B2C etc.)

I can also give a second opinion on your organization’s digital activity; there’s often much unseen inefficiency and I’ve always been able to find improvements.

I hope it’s helpful to note downsides I’ve directly observed in some digital marketing agencies (surprisingly, even firms with strong reputations):

• Payment incentives may work against your goals. e.g. taking a percentage of ad spend as a fee pushes an agency to spend, rather than working hard to boost cost-efficiency

• Using a cookie-cutter approach across diverse clients (even when it fails to align to a specific company’s characteristics)

• The agency business model works via:

  • Attention spread across many clients

  • Utilizing junior resources to do most of the actual work

• I’ve witnessed further issues prior to myself taking over from agencies. For example:

  • Much wasted spend. Not optimizing granularly, rather relying on default settings or auto-optimization even when failing to achieve targets

  • Degraded performance KPIs (e.g. doubling customer acquisition cost)

  • Overlapping targeting, incorrect campaign types/settings, messiness, inaccurate reporting, failing to notice or resolve problem areas, simplistic optimizations that reduce revenue (e.g. turning off a campaign instead of bringing it to profitability)

  • Too-broad targeting bringing unqualified traffic/users that never become customers. e.g. I saw an agency target 1/3rd the U.S. population for a niche product, with many [unqualified] emails harvested but not a single sale generated!

  • Lacking basic hygiene: Forgetting to turn off promotional ads, taking too long to make crucial changes (like budgets), sloppy/off-brand ad copy or typos, etc.

Yes, certainly. I have set up digital ad platforms from scratch for new businesses (even my own entrepreneurial activities), several times in the past. I’ve deployed budgets as low as $75, to as high as $60k daily. I love helping scrappy businesses with great products or services, to find new customers.

I’ve built the entire infrastructure: creating ads messaging, building campaigns, engineering diverse audiences, setting up conversion events/tracking/GA4, forecasting, budgeting, custom reporting and insights.

All of them: I have deep experience of Google, Youtube, Facebook/Instagram, other paid social, content syndication, content recommendation ads, browser-specific, mobile ads, SaaS/3rd party providers for specific targeting/reporting etc.

The choice of platforms, and how they’re used, must be tailored to the nature and goals of the individual business. Not all are recommended nor potentially successful.

One example in B2B lead generation: Facebook prospecting ads traffic costs a fraction vs. Linkedin. However, Linkedin’s more precise job-title (among other professional) targeting, is often still more cost-efficient when looking at cost-per-lead and lead quality. Of course, it’s good to test both.

Search ads are very powerful because they capture the intent of users ‘solving a problem’ in the moment. There’s also more granular control over targeting and the cost of traffic.

Also, a bit technical but makes a huge impact on successful spend allocation: I model-out ‘apples-to-apples’ truer comparisons of performance between different platforms and their diverse attribution models (e.g. Facebook’s max 7-day conversion window, vs. Google Search’s superior 90-day window). This is crucial to understand what success means and allocate capital effectively among diverse activities.

Yes. I have experience writing copy for diverse industries, strategizing numerous ad formats and even working with design agencies. I’m also experienced at finding the correct ‘hook’ via generating and testing diverse themes.

A major priority is understanding business characteristics, brand, and customers. I enjoy working with the team to build creatives, then testing iteratively for continual improvement over time.

Yes, in selected cases I’ve used manual bidding because it improved efficiency (ROI) or even brought a failed campaign to success. It’s another option in the toolkit (which is often ignored because it takes more analysis, work and expertise). The “Google Ads: Optimizing Search For Higher ROI” in case studies will aptly illustrate one example.

Auto-bidding automatically adjusts bids on ads in real-time based on the likelihood of the ad being clicked or leading to a conversion. Needless to say, this is quite powerful assuming the algo has enough data to work with. It’s always the default setting (e.g. Google Search campaigns) but I’ve seen several situations where the extra effort of human knowledge and manual bidding calculations work much better:

1. Not enough data for the algorithm to be effective at statistically predicting the quality of that next click. The campaign may overspend without value generated, or throttle down to zero spend when it fails to reach the goal (e.g. CPA target). Even with enough conversion data (e.g. a remarketing audience in YouTube ads), I’ve found that manual bidding can be much more efficient; e.g. you’re telling Google, don’t spend more than 0.03 per video view because beyond that, the ad group will be unprofitable.

2. More control: e.g. if you are targeting a specific audience or product, you might want to manually set higher bids for those ads to increase the chances of them being seen by your target audience.

3. Auto-bidding algorithms may not take into account all the factors that are important to your business. By using manual bidding, you can make sure that you are taking all the relevant factors into account when determining bid amounts. (e.g. incorporating the quality of the conversions like B2B leads, bounce rates in eCommerce traffic, profit margins, LTV etc.)

As always, It's important to evaluate the specific needs and goals of the business and the campaign data to use the method that will work best.