Medium Data ROI Beats Big Data

Fortune 2000 companies wield big data to achieve marketing ROI that crushes competition. But in a David and Goliath story, Medium Data slays giants.

Medium Data vs. Big Data
David and Goliath (from catholicteacherresources.com)

Here I aim to coin the term “Medium Data” and explain why it can achieve higher ROI than Big Data.

By now even the general population has a sense of what “Big Data” is, but most web marketing executives don’t see how far Big Data reduces the marketing cost of acquiring new and repeat customers. Artificial intelligence (AI) and its subspecies machine learning accelerate the speed of gathering and using not only mainstream data like credit card purchases and browsing history, but also far-flung and spotty data, like patterns of proximity to stores or timing of boarding a flight to Rome. Economies of scale in AI-driven marketing automation–including on-the-fly prioritization of web page content–increasingly propel top corporations’ ROI. But the sling and stone of Medium Data deployed by a canny David can at least drop Goliath to one knee.

The stone is data you already have or can acquire easily. The sling is new platforms like Google Big Query and Data Studio. David is the warrior who knows how to use this weapon. Look, there are diminishing marginal returns from the more difficult to acquire and disparate data. Applying advanced digital marketing knowledge to only the most important sets of data means less “I” (investment) than with Big Data, raising your ROI above Goliath’s.

An Example of Medium Data in Action

Imagine this: Using Medium Data, you discover three topics and 30 pages of your website that, given a relatively small amount of SEO work, will produce over double the ROI of any other marketing channel you used in the past. Before medium data, you could have discovered this opportunity by stitching together sources such as Google Analytics, Search Console, search engine rank, and keyword difficulty scores. That’s what good search marketing firms have done for years. But now, with Google’s revolutionary new tools in G Suite and with new APIs for importing diverse data, we can do better..

Now Medium Data–gathered via APIs into Google Sheets and a Big Query database, then analyzed in part by free AI, then rendered and clearly displayed by Data Studio–reveals your most cost-effective next steps within or among marketing channels, like SEO, PPC, CRO, or email marketing. The requisite data has long been available to you but it was too difficult and expensive to gather and analyze. Examples of this data are InLinks per page, conversion rate by types of click path through your site or by browser or by demographic attribute, average page load time, average profit per offering, and recent trends in competitors’ advertising spend. In Medium Data, expertise earns its place at your table by knowing what data to select and how to weigh and correlate it in order to reveal your next best move.

For years firms have offered software that uses Medium Data, but it starts at $3,000 a month and goes way up from there. Google has “disintermediated” many marketing models, like radio and newspaper advertising, and it’s happening again in the arena of such software.

Your Smartest Next Move

Obviously I want you to contact DISC to explore your options here. But with or without DISC, your next best move is to get David and his sling and stone on your side.

Google’s Panda Algorithm Update: Is it Grizzly or Good for You?

Google Panda Bear

Was Google Panda Good for You?

The lessons of Google’s Panda algorithm update launched on February 24 are simple:

Grizzly Google Panda Update

Or Grizzly?

(1) Don’t do black hat SEO.

(2) Think hard about the risks of grey hat SEO.

(3) Do what Google tells you in their extensive guidance pages.

(4) Design good website usability. That is, put your human audience front and center.

Google’s Panda update justly punishes sites that have more than one of the following, but a single item that is especially abused may be enough alone to cause demotion:

  1. Scraped (or stolen) text content.
  2. Websites with lots of pages without unique content. When there are too many such pages, probably the whole site is demoted, not just those pages or categories.
  3. Excessive SEO keywording.
  4. Excessive intra-site links.
  5. Maybe more punishment then prior based on poor incoming links, according to some researchers.
  6. Maybe poor code. If not, expect this to play a greater role over time, because Google rightly assumes some correlation between a site with good code and a site with good content.
  7. Poor usability. It’s unclear what site features Google’s algorithms would identify as a proxy for poor usability, but here again, it makes sense that Google would see a correlation between good usability and searches being satisfied with Google when the searchers find first a site that pleases the brain.

Some of the above items are debatable and still being investigated by SEO researchers (including DISC), but the consensus is that items 1 through 4 almost certainly prompt demotion. And they all entail black hat or grey hat SEO.

White hat SEO endures for years, without risks which reduce the current value of your company. DISC has always practiced white hat SEO, and so far we have not found a single current client of ours punished by Panda (although a long dormant client who did much of their own SEO has come back to DISC for help in redressing a 40% drop in business starting on the day Panda went live).

In some forms of managerial accounting, risks are factored into ROI projections of capital investments and into the current value of the company. This logic applies to investments you have already made, so that the risks of those investments failing at any time in the future reduce the current value of your firm. Some simple math illustrates this principle.

  • $100,000 capital investment (in a new machine or in SEO, for example) is predicted to improve profits by $500,000 in one year.
  • But there’s a 50% risk of failure (in equipment or SEO) causing, in turn, a 50% reduction of the $500,000 ROI.
  • This means $275,000 ROI, not $400,000 (subtracting the $100,000 investment from the pre-risk-adjusted $500,000 increase in profits)

However, black or grey hat SEO can risk decreases in current organic-based profits, never mind the risk of not achieving increases. That math looks like this:

  • $100,000 capital investment in SEO is predicted to improve profits by $500,000 in one year.
  • But there’s a 50% risk of failure in SEO causing no increases and a 50% reduction of the, say, current $1,000,000 in annual organic-based profit.
  • This means negative $100,000 ROI (loss), which is $600,000 less ROI than would be the case if you eliminated the 50% risk.

While it is impossible to predict exact ROI and risks, the principle of risk nonetheless holds, and it should guide your SEO investments. If you take no SEO risks and, per Panda, you invest in website usability as well, or if you invest in eliminating all current risks, then the present value of your company rises immediately.

Business, like equity investments of all kinds, is all about reducing risks. Less risk of future losses via white hat SEO and usability enhancements adds current value to your business portfolio — and certainly to your peace of mind.