Strategy - Recent Learning's

The past few weeks have been focused on.

• Data Science Strategy Roadmap
• Better Slides / Multiple perspectives
• Balancing Deep Dive vs Strategy
• Timelines vs Options
• Available time vs Options

A lot of content - preparation - presentation. Feels like a blend of product manager role + Database Developer + Creative Team.

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Stats about sqlandsiva blog since Jan 2022

Engagement Stats

• Average session time - 2 mins
• Page views are approx 1.5

Max visits by Country

Most of the session is a very short duration

A lot of searches seems to happen to look for content

Authorize lookr to connect data

Nice charts to export and Analyze

I love Grammarly insights as well. It can read beyond the lines :)

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AWS - Personalization - Good Read

Personalize cross-channel customer experiences 

Key steps

• Collect data from multiple sources to store in Amazon Simple Storage Service (Amazon S3).
• Use AWS Step Functions to orchestrate data onboarding and feature engineering.
• Build segments and predictions using SageMaker.
• Use propensity scores for display targeting.
• Send personalized messaging using Amazon Pinpoint.
• Integrate real-time personalized suggestions using Amazon Personalize.

Code Examples - Link

User Segmentation - Link, Amazon Personalise

Data sources connect to AWS Kinesis Link

Build, tune, and deploy an end-to-end churn prediction model using Amazon SageMaker Pipelines

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How all Web Analytics data is stored ?

Google Analytics data is stored in a proprietary database and is not accessible to query as a SQL query.

Salesforce Analytics data is stored in a proprietary database called Wave. It is not accessible to query as a SQL query. Instead, it is accessible through the Salesforce Analytics Query Language (SAQL) which is a specialized language for querying and manipulating data stored in Wave.

Tealium analytics data is typically stored in a NoSQL database, such as MongoDB or Cassandra. It is not accessible to query as a SQL query. However, Tealium does provide an API that allows you to access the data programmatically.

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CDP - Key Data Pointers

Typical Customer Data Points - Signals

Building a Customer profile

Similar Audiences

Personalization for different audiences

Ref - Link

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Ideas - create exceptional customer experiences - Retail

You need to have a truckload of ideas. This interesting report has a lot of insights on areas to focus on.

Ref - Link

Some key pointers

Touch point-based analysis

Customer feedback-based Insights

Competitor based comparison

Impact of each level of engagement

Ref - Link

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Insight vs Perspective vs Story

Data from Analysis vs Insight

Ref - Link

Charts and when to use 

Storyflow

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Communication - Presentation Tips

Key Pointers / Collated from bookmarked reads

• Bringing your best communication flow
• Imitate the pace of your favorite speaker. 
• Intentionally speak slower if you speak faster 
• Vary Your Speed 
• Share your thoughts and insights over time along the flow
• Be prepared to Practice Under Mild Stress
• The less you rely on notes for your final presentation, the more eye contact you'll make
• It's not always comfortable watching yourself on camera, but it's a critical tool for successful presentations.

An effective presentation can be your competitive weapon too

A great presentation can do so many things: launch careers, inspire employees, and attract customers and investors, and partners. 

Read more at: Link1, Link2, Link3

• Strategy Consulting Firm Presentations
• Choose the Roadmap Template You Need
• Boosting your productivity

Everything has a key message to attract/retain attention 

Powerpoint mistakes

• Use a professional font like Arial (12/14 font size)
• Minimum and consistent use of font colors
• Highlight/underline the key point that you wish to make
• Have margins all around the slides so that it can breathe 
• Alignment of the text and the elements in the slide
• Each slide should also have a slide number
• Each slide should have a source in the bottom section that provides the source of the information

Finally writing some of the key dos and don’ts of Presentations

• Refrain from using fancy graphics and animations in the slides
• Only use professional fonts with minimal use of colors
• Never go multicolor with your presentation; graphs and illustrations throughout the deck should have common and sophisticated colors
• Make sure that the text within the slides is in the margins and doesn’t spill over
• Action titles should not be more than two lines
• When you are copying some information from Google/web after your research, make sure that the source is provided; else it is considered plagiarism
• Format, format, and format your slides

Ref - Link

People have a very short attention span. we need engage with the right weapons

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GAN Limitations

 

Good Read - Limitations of GAN

Ref - Link

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Build your circle carefully

Some projects will transform you from a caterpillar to a butterfly
Some projects will transform you from a butterfly to a caterpillar
Some managers will transform you from a caterpillar to a butterfly
Some managers will transform you from a butterfly to a caterpillar
Some friends will transform you from a caterpillar to a butterfly
Some well-wishers will transform you from butterfly to caterpillar

Choose your environment

Keep Thinking!!!

How to prioritize features / backlogs ?

• Value vs effort - Balance effort vs impact on product/business
• Look at impact across - Specific clients, segments, industries

Techniques

• RIC - Reach * Impact * Confidence
• MoSCoW - M for Must Have, S for Should Have, C is for Could have, W for Won't have

Ref - Link

Ref - Link

Ref - Link

Type of Workshops

• Discovery workshops: Communicate the current state and create consensus for milestones and plans
• Prioritization workshops: Build consensus on which features customers (or other stakeholders) value most and prioritize them

Ref - Link

Ref - Link

Features are added under their respective activities and ranked according to necessity.

Product management frameworks

Ref - Link

Personalization at page level

More Reads

• Feature Prioritization: 7 Ways to Prioritize Features and Product Improvements
• 3 Prioritization Techniques All Product Managers Should Know

Ref Link

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Good Read - How to know what customers need

Ensemble of - Data Science =  1/3 engineers, 1/3 MBAs and 1/3 social scientists

• While initial reports of customer satisfaction were positive, the strategy proved to be a failure.
• Avoid copying your competitors' solutions. Instead, create solutions tailored to the specific needs of your customers.
• When conducting customer interviews, avoid asking "yes/no" or leading questions that limit their responses.
• Don't survey customers with preconceived notions of their answers, or you’re likely to run into confirmation bias.
• Instead of asking customers what they want, focus on what they actually do.

 Ref - Link

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How can personalization go wrong

There are many reasons why personalization doesn't happen or goes wrong:

• wrong technology stack
• lack of human and financial resources
• complexity of data
• handling personalization as a one-shot game instead of treating it as a process

major consequences of wrong personalization:

• loss of customer trust because of a breach of privacy
• frustration due to facing irrelevant content and messaging

Ref link

The value of getting personalization right—or wrong—is multiplying

• Thoughtful touchpoints such as checking in post-purchase, sending a how-to video or asking consumers to write a review generate positive brand perceptions.
• When asked to define personalization, consumers associate it with positive experiences of being made to feel special. 
• They respond positively when brands demonstrate their investment in the relationship, not just the transaction

Ref - Link

• 64% of organizations are either not collecting data or are storing it in siloed systems, resulting in disjointed experiences for customers.

Multiple-variable customer segments

multiple-variable customer segments group customers by sets of traits or behaviors they have in common, rather than only one. An example might be a customer who:

• Is from Japan
• Has never transacted before
• Has an interest in the headphones product category
• Is female, age 25-30

it’s more realistic to start with small, incremental improvements. Little wins add up, and they also provide insights you can use to fine-tune your strategy and content.

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Layoff - Analysis

Some key things we need to understand 

• Hiring people to avoid giving talent to competitors
• Feels scared are the trends are real trends but distracting competition
• Unable to track/understand trends / Far from reality
• Is this a consequence of Over hiring - Without clarity of perspectives
• Working on an Idea that never has a market - Metaverse / Bitcoin 
• Big companies build LLM - Focused startups pick and solve domain problems

Keep Thinking!!!

 

2023 Future Today Institute Trends report

Critical insights from Future Today Institute report 

• AI Impact continues to dominate all sectors in the near term. It is long-term 1~2 years. Adoption takes time
• Metaverse I do not see any focus from Microsoft or Meta. This I would move to recycle bin

Key questions across sectors

News and Media

Supply Chain Trends for this Year

Supply Chian questions to pick priority

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GAN Vision Startups

Ref - Link

Selected Vision Investments

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What a Life

Trying to find similar groups based on behavior - Apply Clustering
Predicting the intuition, this is my job connecting to it - Classification
With a new height of happiness/hope in life - Forecast more sleep hours
Look at people, decode their intentions - Read data/correlate and spot intentions
Finding my liked-minded folks with cosine, euclidean, and manhattan but still not getting relevant recommendations
On mistakes still learning to backpropagate and change/improve my optimistic learning rates
Everything is deep in life... the deeper you feel, the farther you go...
Have more attention to the present. Live more, Feel the Life.

It's a Deep Life :)

Recommendation - Distance Measures

 

Ref - Link

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Keep Saas Domain MVP Skills as Expertise

Less ambitious about titles, curious about technology, its age of knowledge, and saas beyond titles and roles - Future Careers

• Little expertise - Knowing how to use, Demos
• Deep expertise - Where to use, How it works, Where not to use
• Deep expertise is - Is this hype or relevant

 

• Getting better sometimes takes time, iterations, and cycles.
• Knowing a domain/idea, being able to code up, speak is all the skill we need :)

The core of Learning is

• Daily Habit formation
• Compare your growth over time
• Similar situations / Never materialized
• Building intuitions is the outcome of 10K hours
• Teaching helps ok at something to getting a better
• Iteration and thoughts formulation
• 10 hours to create 1-hour content
• Teaching strengthens understanding, spots gaps in knowledge

What are you working on to become a better programmer?

• The domain learning's, customer challenges will push our interests to continue to practice solving real-world problems 
• Breaking the problems down into discrete chunks that can be independently implemented
• You waste more time jumping into a program without direction by solving only interview questions
• Most people make the mistake of jumping straight to code without having the full picture in their heads
• "getting stuff done" at work and "perfecting the craft" in my spare time is an attempt to strike a balance: Think about the design, leave things nicer, but don't spend forever.
• Perfecting the craft leaves you to read up, teach, and code on weekends :)
• A balance between perfect vs good enough vs working solution

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Notes - Recommendation Metrics

Setting Goals and Choosing Metrics for Recommender System Evaluations

• Number of items that are either relevant or irrelevant and either contained in the recommendation set of a user or not
• How many of Top K contains relevant items

• If the recommendation list contains only relevant items, then the area under the curve is in fact zero
• Relevant items that are retrieved at the end of the list with no irrelevant items following do not add to the area under the limited curve.

• A top-k list that contains more relevant items will yield a higher score than a list with less relevant items
• How many of Top K contains relevant items. If the recommendation list contains only relevant items

Common metrics to evaluate recommendation systems

ROC Curve

A ROC curve plots recall (true positive rate) against fallout (false positive rate) for increasing recommendation set size

• True Positive items are therefore the items that you showed in your Top-N list that match what the user preferred in her held-out testing set
• False Positive are the items in your Top-N list that don't match her preferred items in her held-out testing set
• True Negative items are those you didn't include in your Top-N recommendations and are items the user didn't have in her preferred items in her held-out testing set.
• False Negative are items you didn't include in your Top-N recommendations but do match what the user preferred in her held-out testing set. 

Classification: ROC Curve and AUC

On Sampled Metrics for Item Recommendation

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