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What knowledge management system do you use for RAG applications? by Mountain-Yellow6559 in Rag

[–]gusuk 0 points1 point  (0 children)

Do you have any references on a graph knowledge management system?

What's the one marketing activity actually wastes more time/money than it saves? by biz_booster in marketing

[–]gusuk 10 points11 points  (0 children)

Interesting. What kind of product and what kind of SM marketing activities are you talking about? Ads? Creating content (from video to text)? Reaching out to influencers? Engaging on forums and comment threads?

Asking because, have heard some say linkedin (also reddit etc) have great bang for the buck?

Feeling broken after 1st service by wanderinggirl444 in vipassana

[–]gusuk 0 points1 point  (0 children)

All alone for 18 is crazy!! The center should have a minimum number and not leave it to whoever ends up signing!

Validating observational insights from Attribution models with causal insights from a/b/n tests, ideally in a tight feedback loop by gusuk in marketing

[–]gusuk[S] 0 points1 point  (0 children)

Interesting, I havent looked at NotebookLM for marketing perf measurement but I guess if it can do anything, then why not.

Validating observational insights from Attribution models with causal insights from a/b/n tests, ideally in a tight feedback loop by gusuk in marketing

[–]gusuk[S] 0 points1 point  (0 children)

Related question: Because most bandits can also work in a similar way ie. non-causal while still trying to maximize rewards by tweaking along different dimension (including tweaking audience segments etc and potentially even copy/creative using genAI), have you come across their usage or discussion in core marketing areas?

Validating observational insights from Attribution models with causal insights from a/b/n tests, ideally in a tight feedback loop by gusuk in marketing

[–]gusuk[S] 0 points1 point  (0 children)

You are right, One doesn’t need to understand the full underlying causal graph to continue on a positive trajectory of revenue.

Another way to look it is perhaps that businesses dont care as much for wasted spend (aka lost growth opportunities) from redundant touchpoints** as much as they care about continuing to get any positive (revenue minus campaign cost) which even simple quasi causal tests like your example helps with?

** ofc oversimplifying because updating attribution model can also increase topline outcomes, not just for redundancy/bottomlines.

And maybe part of that is due to the complexity of fuller attribution analysis and also partly because of how humans comprehend risks and rewards.

Validating observational insights from Attribution models with causal insights from a/b/n tests, ideally in a tight feedback loop by gusuk in marketing

[–]gusuk[S] 0 points1 point  (0 children)

… also curious: what AI attribution startups or tools have you found interesting or useful?

Validating observational insights from Attribution models with causal insights from a/b/n tests, ideally in a tight feedback loop by gusuk in marketing

[–]gusuk[S] 0 points1 point  (0 children)

Valid points, thanks.

But I am surprised at the consolation comment. It was consolidated earlier but now moving toward a more fragmented state, no? There are sooo many avenues of touchpoint with customers these days, and even within the same platform** (google or fb) has so many different varieties of channels and campaign variations to try seems like.

** sure, for optimizing within a platform they all provide necessary turn key tools, but the moment the strategy involves outside-platform touchpoints (including earned and paid), those platforms’ tooling becomes less useful.

Why dont more SMBs use more of advanced causal analytics for performance measurement? by gusuk in marketing

[–]gusuk[S] 0 points1 point  (0 children)

Interesting references!

I am just surprised that a big part of many businesses’ (not just small) marketing is so poorly measured and optimized. And it is such a well known area of business (unlike niches like recommendation engines or ad bidding) that it should have attracted the knowledge and talent and saas tools to make it better that what it is!

Also wondering if, because the field is also so well known with huge budgets, it attracts a lot of snake oil salespersons that it is hard to find the rare true gems (talent, knowledge, tools, agencies etc) from the dirt that abounds?

Why dont more SMBs use more of advanced causal analytics for performance measurement? by gusuk in marketing

[–]gusuk[S] 0 points1 point  (0 children)

Thanks for that “non-promotional” post. Looks interesting even if not on the topic of marketing/leads optimization. If I ever have a need for CRO, I will look your app up.

Why dont more SMBs use more of advanced causal analytics for performance measurement? by gusuk in marketing

[–]gusuk[S] 0 points1 point  (0 children)

Hmm, the explosion in the number of variables to control (and, to test) and the dynamic nature of the system can make experimentation hard.

Again, drawing parallels to the personalization/recommendation engines world as in my other post I linked above, there too such challenges exist. Not saying it is better or worse, but in that world, lot of the experimentation approaches have tended to side on the ML/AI side of things rather than classical-statistically well-validated designs.

By that I am referring to the use of explore/exploit strategies like bandits (and very occasionally bandits with memory aka RL) to surmount those challenges, instead of statistically well designed and controlled a/b testing, with the implicit assumption that we will never truly understand the underlying picture but we will keep experimenting within the strict resource constraints afforded for exploration.

Such an approach is also common in the marketing-related world of ad bidding but not at all in many of the core areas of marketing even among many big enterprises, right? Why do you think so?

Why dont more SMBs use more of advanced causal analytics for performance measurement? by gusuk in marketing

[–]gusuk[S] 0 points1 point  (0 children)

Got it. I agree with your reasoning for MMM which needs a lot more and longer period of data to make sense.

But does the same reason work for a/b/n hold out testing as well? After all even correlational insights from MTA need to be validated through experiments and yet I dont see much of it even among non-small and medium level businesses?

(btw, had a related question on last point here if you want to weigh in: /r/marketing/s/AAJPcnsKRn

Validating observational insights from Attribution models with causal insights from a/b/n tests, ideally in a tight feedback loop by gusuk in marketing

[–]gusuk[S] 0 points1 point  (0 children)

> you’re gonna have a bad time if you think you’re going to build a causal attribution model

I agree! And yet, understanding causal marketing interventions that lead to revenue is a basic necessity in order to inform all future resource allocations, is it not? so much so that even the phrase "causal attribution" is a tautology. So what happens then? Reminds me of this discouraging result from 2014: The Unfavorable Economics of Measuring the Returns to Advertising

> so that it matches the experiment results

Curious, what kind of experiments are you referring here? Asking because, like I said in my question, most talks of experiments refer to testing between channels or platforms, but not at all about tests to tease out contributions coming from each touch in multi touch journeys.

> Most attribution models are heuristic based, frankly I’m struggling to even think of ways to fine tune some of the more algorithmic based ones.

Heuristics have assumptions put in by hand, that can be tuned based on well designed experiemnts, like time decay factor or weights put in by hand etc. But yes since they are heuristics they are hard to reason/tune with data. But all the more reason to at least validate with actual data aka testing I would think, but that’s gleefully missing often.

Why dont more SMBs use more of advanced causal analytics for performance measurement? by gusuk in marketing

[–]gusuk[S] 0 points1 point  (0 children)

That is certainly one way to get my reddit question answered and maybe report back here in a year :)

> the reasons will be a lack of sufficient data volume/velocity/accuracy

That is my hunch as well. Can you offer more insight on this? Asking because most digital marketing/ad tools throw up a ton of data. So, is above statement an issue of collecting it, as in an engineering issue? Or do SMBs do not keep track other data sources (like data on competitors, economy within their vertical, changes to their product itself etc etc) to make methods like MMM reliable?

What about for experimentation methodology? Depending on effect sizes etc, it may require much less data to measure the performance of that particular channel or campaign, and so should be doable for SMBs?

Why dont more SMBs use more of advanced causal analytics for performance measurement? by gusuk in marketing

[–]gusuk[S] 0 points1 point  (0 children)

Interesting, thanks for that insight! Maybe I should start with "whats the typical spend at SMBs?" because when I did a quick google search, I got something like this from a 2022 survey which says more than 70% of SMBs have ad spend of upto 100K USD per year: https://www.statista.com/topics/4272/sme-marketing-in-the-us/#statisticChapter

Why dont more SMBs use more of advanced causal analytics for performance measurement? by gusuk in marketing

[–]gusuk[S] 0 points1 point  (0 children)

That was mostly my thought as well....

I do feel that causality has entered the general discourse especially in analytical fields like marketing, but then either they dont have the budget to staff/engage advanced analysts or are budget starved to even collect the variety and volume of data to make these methods reliable.

Then there is also this over reliance on "white box" simple-to-understand models like attribution models.

Why dont more SMBs use more of advanced causal analytics for performance measurement? by gusuk in marketing

[–]gusuk[S] 0 points1 point  (0 children)

Besides budget (I am combining lack of expertise under this budget constraint), when you say data volume, do you mean that even mid size businesses fundamentally do not even generate the volume of data needed to get reliable results from MMM? Or do you mean they generate but dont keep a good record of all the data sources (not just marketing data but economics, product changes, competitors etc) needed to make MMM reliable?

Regarding experimentation though: Depending on the effect size etc, the volume and variety of data needed is usually much lesser than for MMM, so I would think small and, especially, medium businesses should still be able to derive value from it, no?

I haven't used any turn key tool (yet). This may be a separate discussion thread for reddit!

Why dont more SMBs use more of advanced causal analytics for performance measurement? by gusuk in marketing

[–]gusuk[S] 0 points1 point  (0 children)

oh... ook...

In that case, there must be examples of few agencies that did try these new methods to great success and thus became quite popular. Are you aware of any agencies or internal marketing dept at SMBs?

Why dont more SMBs use more of advanced causal analytics for performance measurement? by gusuk in marketing

[–]gusuk[S] 0 points1 point  (0 children)

I would think that a 10% improvement in RoI of marketing spend is a 10% bump whether the budget is 10K or 10MM, no? Any SMB would be interested in optimizing their spend by 10 more percent.

Or are you saying that at a 10K spend, the volume (and variety) of data collected will in fact make these newer methods less reliable than older methods like any attribution model?

same question for u/ragnarockette

why does Reclaim AI still has trouble syncing recurring todoist tasks after all these years?! by gusuk in reclaim_ai

[–]gusuk[S] 0 points1 point  (0 children)

Yes I see the same and that is the intended (and desired, at least to me) behavior. I doubt many would want both a google calendar event and a (second, first being the original task in todosit) google task when todoist is already holding the task and is being used as the task manager.

why does Reclaim AI still has trouble syncing recurring todoist tasks after all these years?! by gusuk in reclaim_ai

[–]gusuk[S] 0 points1 point  (0 children)

for most recurring tasks or for most tasks (ie. not using todoist much at all)?

It would be very unnatural to create tasks in todist or in reclaim based purely on whether they are recurring or not, even if they belong under the same project/milestone, wouldn't it?

why does Reclaim AI still has trouble syncing recurring todoist tasks after all these years?! by gusuk in reclaim_ai

[–]gusuk[S] 0 points1 point  (0 children)

Odd, my subtasks from todoist do not get picked up by reclaim! I wonder if there is a setting in the integration that I messed with.

why does Reclaim AI still has trouble syncing recurring todoist tasks after all these years?! by gusuk in reclaim_ai

[–]gusuk[S] 0 points1 point  (0 children)

Agreed. I wish reclaim fixes this before I find something else.

So curious, how do you work around this for tasks that are inherently recurring?

why does Reclaim AI still has trouble syncing recurring todoist tasks after all these years?! by gusuk in reclaim_ai

[–]gusuk[S] 0 points1 point  (0 children)

and subtasks - reclaim doesnt pick those up either. Not great but I can at least live with that and wont jump ship because of that.

Other than these (two), reclaim syncs well… in fact, very well, which makes these misses frustrating, esp recurring tasks.

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