A SlideShare that quickly explains three essential ways marketers can leverage data analytics to make more effective decisions and drive more favourable outcomes.
Conquering Customer Analytics in Retail - InfographicOpenbravo
Data is a terrible thing to waste and, unfortunately, that is exactly what retailers are doing with a resource of inestimable worth. The present state of analytics in retail is, in a nutshell, underutilized.
A SlideShare highlighting how predictive customer journey analytics – also known as behavioural modelling – allows marketers to analyse previous behavioural patterns and more accurately predict what customers will do next
Marketing analytics is the study of consumer data to evaluate marketing performance and optimize campaigns. It involves collecting, cleaning, and analyzing consumer data using statistical techniques to understand consumer behavior, refine marketing strategies, and predict future trends. Marketing analytics helps target consumers based on their interests and serve them the right messages at the right time through the right channels. It evaluates past marketing performance, reports on previous campaigns, and predicts future trends to improve marketing plans.
This document provides information about a session on clickstream analysis and web analytics. The session aims to provide students with an understanding of clickstream data collection, analysis, and interpretation to optimize digital experiences. Key topics covered include clickstream analysis, multiple outcome analysis, experimentation and testing, competitive intelligence, and incorporating customer feedback. The session learning outcomes are for students to apply clickstream data to improve digital experiences and use competitive intelligence to inform decision-making.
The document discusses setting up an effective analytics framework. It outlines eight key phases: 1) attributing traffic sources, 2) defining the sales funnel, 3) integrating data, 4) attributing conversions, 5) optimizing conversions, 6) segmenting prospects, 7) analyzing the post-purchase funnel, and 8) ongoing reporting. It emphasizes regularly analyzing data and taking action. The goal is to understand customer behavior and improve revenue. Setting up the right analytics framework requires auditing current data, developing a collection strategy, and ongoing reporting and analysis.
In this presentation, we will explore the importance of tracking and
measuring content syndication campaigns. Discover key metrics, tools,
and techniques for tracking and optimizing campaign results
Marketing analytics is the practice of measuring and analyzing marketing performance to maximize effectiveness and ROI. It provides insights into customer preferences beyond basic sales and leads. However, most organizations fail to realize its full benefits. Marketing analytics considers all marketing efforts across channels over time, which is essential for sound decision-making. It allows monitoring of campaigns and spending to see what is most effective. Knowledge of returns on marketing investments is important for long-term business strategy. Marketing analytics software continues to evolve and provide more powerful insights.
Conquering Customer Analytics in Retail - InfographicOpenbravo
Data is a terrible thing to waste and, unfortunately, that is exactly what retailers are doing with a resource of inestimable worth. The present state of analytics in retail is, in a nutshell, underutilized.
A SlideShare highlighting how predictive customer journey analytics – also known as behavioural modelling – allows marketers to analyse previous behavioural patterns and more accurately predict what customers will do next
Marketing analytics is the study of consumer data to evaluate marketing performance and optimize campaigns. It involves collecting, cleaning, and analyzing consumer data using statistical techniques to understand consumer behavior, refine marketing strategies, and predict future trends. Marketing analytics helps target consumers based on their interests and serve them the right messages at the right time through the right channels. It evaluates past marketing performance, reports on previous campaigns, and predicts future trends to improve marketing plans.
This document provides information about a session on clickstream analysis and web analytics. The session aims to provide students with an understanding of clickstream data collection, analysis, and interpretation to optimize digital experiences. Key topics covered include clickstream analysis, multiple outcome analysis, experimentation and testing, competitive intelligence, and incorporating customer feedback. The session learning outcomes are for students to apply clickstream data to improve digital experiences and use competitive intelligence to inform decision-making.
The document discusses setting up an effective analytics framework. It outlines eight key phases: 1) attributing traffic sources, 2) defining the sales funnel, 3) integrating data, 4) attributing conversions, 5) optimizing conversions, 6) segmenting prospects, 7) analyzing the post-purchase funnel, and 8) ongoing reporting. It emphasizes regularly analyzing data and taking action. The goal is to understand customer behavior and improve revenue. Setting up the right analytics framework requires auditing current data, developing a collection strategy, and ongoing reporting and analysis.
In this presentation, we will explore the importance of tracking and
measuring content syndication campaigns. Discover key metrics, tools,
and techniques for tracking and optimizing campaign results
Marketing analytics is the practice of measuring and analyzing marketing performance to maximize effectiveness and ROI. It provides insights into customer preferences beyond basic sales and leads. However, most organizations fail to realize its full benefits. Marketing analytics considers all marketing efforts across channels over time, which is essential for sound decision-making. It allows monitoring of campaigns and spending to see what is most effective. Knowledge of returns on marketing investments is important for long-term business strategy. Marketing analytics software continues to evolve and provide more powerful insights.
This document discusses how predictive analytics and content targeting can improve the user experience. It defines predictive analytics as examining patterns in data to identify future risks and opportunities. Content targeting provides customized content for users based on their behaviors and attributes. This enhances the customer experience by delivering relevant information. Predictive analytics has various uses, such as reducing churn, increasing sales, and optimizing operations. Case studies show how predictive analytics helped a truck manufacturer anticipate breakdowns and a retailer increase revenues through audience segmentation and recommendations. The document advocates for strategic content targeting over generic content to create a better customer experience.
The six-step guide outlines how to break through the analytics barrier and fully realize the benefits of analytics programs. The six steps are: 1) define customer experience outcomes, 2) integrate a big data infrastructure, 3) rethink the customer journey, 4) enhance insights with digital data and processes, 5) construct solutions from the customer perspective, and 6) test and measure for outcomes. Following these steps helps move analytics initiatives beyond operational reporting to enabling predictive insights that improve the customer experience.
This document provides an overview of marketing analytics. It begins by defining marketing analytics and explaining its benefits, such as insights into customer preferences and trends. It then discusses the types of analytics, including descriptive, predictive, and prescriptive analytics. The document emphasizes the importance of marketing analytics for making data-driven decisions, integrating across channels, understanding customer lifecycles, and tying marketing activities to sales. It outlines trends in marketing analytics, such as becoming more customer-centric and improving online-offline attribution. Finally, it profiles several leading marketing analytics companies and software.
The company provides advanced analytics and data-driven decision making services. It has deep analytical capabilities across various industries, developed custom products, and has an expert team of data scientists, analysts, architects and programmers. The vision is to be a world leader in advanced analytics and enabling technology. Services include marketing, operations, supply chain and risk analytics. The company uses big data technologies like Hadoop and advanced tools to deliver solutions focused on customers across industries.
BrandsLab Marketing Performance Optimization Session 1 | Off the Beaten Path ...Ebiquity-NA
This session uncovers the most under-utilized paths to multi-channel analytics success. From establishing governance structure to identifying technologies, we will help you think more strategically about your business.
MachineLearning_Brick and Mortar Store Layout Design.pptxKishanhari3
The document proposes using machine learning models to optimize the layout of a brick-and-mortar store. It discusses using association rule mining and other techniques to arrange departments and items in a way that maximizes revenue. The proposed technical architecture would involve collecting and preprocessing store sales data, then developing ML models to categorize store zones, items, and recommend new layouts to improve customer flow and sales. Model outputs would provide strategies to apply in different areas of the store to engage customers.
6 Key best practices to enhance Marketing with AISophie LEHMANN
Artificial Intelligence has been around for decades, but has
seen a recent resurgence in interest as data size and diversity
continue to grow and the cloud becomes a popular option for
quickly and economically scaling compute power and data storage.
This Checklist explores how AI can be used to enhance marketing
analytics and to help companies both better understand their
customers and deliver a great customer experience.
Marketing Analytics Meets Artificial Intelligence: Six Strategies for SuccessMiguel Mello
This document outlines six strategies for using artificial intelligence (AI) to enhance marketing analytics and improve understanding of customers. It discusses using machine learning and automation to enable real-time decision making and next best offers. It also covers using AI and machine learning to improve cross-selling and up-selling efforts. Additionally, it discusses using cognitive computing and sentiment analysis to better understand customer feedback and using cognitive computing and natural language processing to enhance customer service. The document also outlines transforming web analytics into digital intelligence and optimizing marketing with analytics and machine learning.
RIS November tech solutions guide - analyticsiinside
Through precise location analytics, retailers now can monitor the entire path to purchase. With this data, marketers better understand what led to the purchase providing the ability to move beyond the traditional blanketed “campaign” to a year-round interaction based on consumer behavior. Customers “opt-in” by mobile app to receive highly-targeted promotions, information about merchandise they may have “visited” but didn’t purchase, and discounts for major events – based on correlations like visits, dwell and intent – to drive sales like never before.
Through precise location analytics, retailers now can monitor the entire path to purchase. With this data, marketers better understand what led to the purchase providing the ability to move beyond the traditional blanketed “campaign” to a year-round interaction based on consumer behavior. Customers “opt-in” by mobile app to receive highly-targeted promotions, information about merchandise they may have “visited” but didn’t purchase, and discounts for major events – based on correlations like visits, dwell and intent – to drive sales like never before.
An online community intelligence audit follows a 4-step scalable process to deliver actionable insights for organizations:
1. Discovery - Define audit parameters mapped to objectives through keyword research and data modeling.
2. Data Modeling - Build and test a data model to ensure data integrity and validity.
3. Measurement - Measure community presence, reach, engagement and influence using benchmark metrics.
4. Analysis - Provide quantitative metrics and qualitative insights through measuring conversations and identifying themes.
The process begins with data collection and sampling to understand where target audiences are active online and validate strategies. Both quantitative and qualitative analysis are used to understand perceptions and conversations to develop effective online strategies. Ongoing audits are recommended
Operationalizing Customer Analytics with Azure and Power BICCG
Many organizations fail to realize the value of data science teams because they are not effectively translating the analytic findings produced by these teams into quantifiable business results. This webinar demonstrates how to visualize analytic models like churn and turn their output into action. Senior Business Solution Architect, Mike Druta, presents methods for operationalizing analytic models produced by data science teams into a repeatable process that can be automated and applied continuously using Azure.
How Analytics drives better Campaigns and a more profitable customer experienceRoger Luxton
This document discusses how analytics can drive better customer experience and more profitable campaigns. It outlines that many companies still lack a single customer view and do not personalize offers. The presentation recommends building a single customer view by collecting all customer data in one place. It then suggests using analytics to focus on key areas like customer journeys. Insights from analytics should then drive more relevant marketing campaigns. Case studies show companies achieving faster analysis, reduced production times, and high returns on marketing investments from implementing these best practices around data, analytics and marketing.
This document discusses the role of marketing analytics in modern organizations. It begins by defining marketing analytics as the collection and analysis of marketing data to understand what initiatives are effective. Common data sources include web traffic, email campaigns, social media, and more. The document then explains how descriptive, predictive, and prescriptive models can be used to analyze past data and optimize future marketing strategies. Finally, it outlines important marketing analytics tools like Google Analytics and skills like data analysis that benefit work in this field.
Revenue Operations Analytics: A Strategic BlueprintKwanzoo Inc
The true value in your KPIs is understanding how they complete the bigger picture of the customer journeys that drive the most impact for your business.
Content marketing analytics: what you should really be doingDaniel Smulevich
My presentation from Digital Marketing Show 2014. #DMSLDN
A journey through web analytics processes, from setting up KPIs to integrating data sources and automating reports.
This document discusses how predictive analytics and content targeting can improve the user experience. It defines predictive analytics as examining patterns in data to identify future risks and opportunities. Content targeting provides customized content for users based on their behaviors and attributes. This enhances the customer experience by delivering relevant information. Predictive analytics has various uses, such as reducing churn, increasing sales, and optimizing operations. Case studies show how predictive analytics helped a truck manufacturer anticipate breakdowns and a retailer increase revenues through audience segmentation and recommendations. The document advocates for strategic content targeting over generic content to create a better customer experience.
The six-step guide outlines how to break through the analytics barrier and fully realize the benefits of analytics programs. The six steps are: 1) define customer experience outcomes, 2) integrate a big data infrastructure, 3) rethink the customer journey, 4) enhance insights with digital data and processes, 5) construct solutions from the customer perspective, and 6) test and measure for outcomes. Following these steps helps move analytics initiatives beyond operational reporting to enabling predictive insights that improve the customer experience.
This document provides an overview of marketing analytics. It begins by defining marketing analytics and explaining its benefits, such as insights into customer preferences and trends. It then discusses the types of analytics, including descriptive, predictive, and prescriptive analytics. The document emphasizes the importance of marketing analytics for making data-driven decisions, integrating across channels, understanding customer lifecycles, and tying marketing activities to sales. It outlines trends in marketing analytics, such as becoming more customer-centric and improving online-offline attribution. Finally, it profiles several leading marketing analytics companies and software.
The company provides advanced analytics and data-driven decision making services. It has deep analytical capabilities across various industries, developed custom products, and has an expert team of data scientists, analysts, architects and programmers. The vision is to be a world leader in advanced analytics and enabling technology. Services include marketing, operations, supply chain and risk analytics. The company uses big data technologies like Hadoop and advanced tools to deliver solutions focused on customers across industries.
BrandsLab Marketing Performance Optimization Session 1 | Off the Beaten Path ...Ebiquity-NA
This session uncovers the most under-utilized paths to multi-channel analytics success. From establishing governance structure to identifying technologies, we will help you think more strategically about your business.
MachineLearning_Brick and Mortar Store Layout Design.pptxKishanhari3
The document proposes using machine learning models to optimize the layout of a brick-and-mortar store. It discusses using association rule mining and other techniques to arrange departments and items in a way that maximizes revenue. The proposed technical architecture would involve collecting and preprocessing store sales data, then developing ML models to categorize store zones, items, and recommend new layouts to improve customer flow and sales. Model outputs would provide strategies to apply in different areas of the store to engage customers.
6 Key best practices to enhance Marketing with AISophie LEHMANN
Artificial Intelligence has been around for decades, but has
seen a recent resurgence in interest as data size and diversity
continue to grow and the cloud becomes a popular option for
quickly and economically scaling compute power and data storage.
This Checklist explores how AI can be used to enhance marketing
analytics and to help companies both better understand their
customers and deliver a great customer experience.
Marketing Analytics Meets Artificial Intelligence: Six Strategies for SuccessMiguel Mello
This document outlines six strategies for using artificial intelligence (AI) to enhance marketing analytics and improve understanding of customers. It discusses using machine learning and automation to enable real-time decision making and next best offers. It also covers using AI and machine learning to improve cross-selling and up-selling efforts. Additionally, it discusses using cognitive computing and sentiment analysis to better understand customer feedback and using cognitive computing and natural language processing to enhance customer service. The document also outlines transforming web analytics into digital intelligence and optimizing marketing with analytics and machine learning.
RIS November tech solutions guide - analyticsiinside
Through precise location analytics, retailers now can monitor the entire path to purchase. With this data, marketers better understand what led to the purchase providing the ability to move beyond the traditional blanketed “campaign” to a year-round interaction based on consumer behavior. Customers “opt-in” by mobile app to receive highly-targeted promotions, information about merchandise they may have “visited” but didn’t purchase, and discounts for major events – based on correlations like visits, dwell and intent – to drive sales like never before.
Through precise location analytics, retailers now can monitor the entire path to purchase. With this data, marketers better understand what led to the purchase providing the ability to move beyond the traditional blanketed “campaign” to a year-round interaction based on consumer behavior. Customers “opt-in” by mobile app to receive highly-targeted promotions, information about merchandise they may have “visited” but didn’t purchase, and discounts for major events – based on correlations like visits, dwell and intent – to drive sales like never before.
An online community intelligence audit follows a 4-step scalable process to deliver actionable insights for organizations:
1. Discovery - Define audit parameters mapped to objectives through keyword research and data modeling.
2. Data Modeling - Build and test a data model to ensure data integrity and validity.
3. Measurement - Measure community presence, reach, engagement and influence using benchmark metrics.
4. Analysis - Provide quantitative metrics and qualitative insights through measuring conversations and identifying themes.
The process begins with data collection and sampling to understand where target audiences are active online and validate strategies. Both quantitative and qualitative analysis are used to understand perceptions and conversations to develop effective online strategies. Ongoing audits are recommended
Operationalizing Customer Analytics with Azure and Power BICCG
Many organizations fail to realize the value of data science teams because they are not effectively translating the analytic findings produced by these teams into quantifiable business results. This webinar demonstrates how to visualize analytic models like churn and turn their output into action. Senior Business Solution Architect, Mike Druta, presents methods for operationalizing analytic models produced by data science teams into a repeatable process that can be automated and applied continuously using Azure.
How Analytics drives better Campaigns and a more profitable customer experienceRoger Luxton
This document discusses how analytics can drive better customer experience and more profitable campaigns. It outlines that many companies still lack a single customer view and do not personalize offers. The presentation recommends building a single customer view by collecting all customer data in one place. It then suggests using analytics to focus on key areas like customer journeys. Insights from analytics should then drive more relevant marketing campaigns. Case studies show companies achieving faster analysis, reduced production times, and high returns on marketing investments from implementing these best practices around data, analytics and marketing.
This document discusses the role of marketing analytics in modern organizations. It begins by defining marketing analytics as the collection and analysis of marketing data to understand what initiatives are effective. Common data sources include web traffic, email campaigns, social media, and more. The document then explains how descriptive, predictive, and prescriptive models can be used to analyze past data and optimize future marketing strategies. Finally, it outlines important marketing analytics tools like Google Analytics and skills like data analysis that benefit work in this field.
Revenue Operations Analytics: A Strategic BlueprintKwanzoo Inc
The true value in your KPIs is understanding how they complete the bigger picture of the customer journeys that drive the most impact for your business.
Content marketing analytics: what you should really be doingDaniel Smulevich
My presentation from Digital Marketing Show 2014. #DMSLDN
A journey through web analytics processes, from setting up KPIs to integrating data sources and automating reports.
The document discusses how first-party data can be used for individualized marketing instead of third-party data due to increasing restrictions on data privacy. First-party data includes contact, behavioral, and transactional data collected directly from customers. It allows for varying levels of individualization from basic targeted offers to advanced personalized messages tailored for each customer based on their preferences. While more accurate than third-party data, first-party data can be difficult for marketers to utilize due to data silos and inability to identify patterns - but using a tool like Apteco can help unlock its full potential.
A quick overview of the most significant trends, challenges and priorities in data and campaign management this year. Based on 200 marketers’ responses at the Apteco Live Online 2021 conference.
The document discusses campaign automation and its benefits over marketing automation. Campaign automation uses data insights to automate personalized, omnichannel campaigns at scale. It improves efficiency by simplifying tasks and workflows, freeing up time for higher-value work. Effectiveness is also improved through personalization and predictive analytics, ensuring the right messages reach the right customers through the right channels. Examples provided include automated birthday campaigns and churn prevention campaigns using predictive scoring.
This document outlines 10 key data-driven marketing pitfalls to avoid. These pitfalls include: lack of company buy-in for a data strategy, keeping data in silos instead of consolidating it, having poor quality data, collecting unnecessary personal data, lack of transparency around data use, focusing on profits over building customer relationships, inconsistent branding experiences, insufficient resources for personalized marketing, poor timing of marketing campaigns, and not tracking customer journeys. The document advocates for data-driven marketing that prioritizes customers, builds trust and long-term relationships through transparency and consistency.
How to create and manage marketing campaigns that promote greater customer engagement.
Looking to build brand loyalty, customer relationships, and overall brand advocacy? It all starts with a focus on personalised marketing campaigns. These campaigns are often part of a wider marketing strategy, but an emphasis on personalisation helps to strengthen the strategy’s overall message.
We’ve put together some examples of multi-channel, multi-stage campaigns that cover a few of the main topics that many businesses want to address. Discover how to engage a customer on a personal level, and how to get the customer to take up a promotional offer.
Digital Marketing Company in India - DIGI BrooksDIGI Brooks
This infographic provides guidance on marketing analytics, helping businesses grow using tools like Google Analytics and AI, measuring ROI, and analysing future trends to track business development.
https://digibrooks.com/digital-marketing-services/
This document was submitted as part of interview process for Marketing Specialist position at DTA Promotion, an Indonesian company which offers 360 degree marketing services, including ATL and BTL advertising platform.
Top Strategies for Building High-Quality Backlinks in 2024 PPT.pdf1Solutions Pvt. Ltd.
As we move into 2024, the methods for building high-quality backlinks continue to evolve, demanding more sophisticated and strategic approaches. This presentation aims to explore the latest trends and proven strategies for acquiring high-quality backlinks that can elevate your SEO efforts.
Visit:- https://www.1solutions.biz/link-building-packages/
3 Best “Add to Calendar” Link Generator Tools (2024)Y
“Add to Calendar” link generator tools allow users to create links that add events directly to digital calendars like Google Calendar, Apple Calendar, and Outlook.
These tools simplify event scheduling by generating short URLs or QR codes that, when clicked or scanned, automatically insert event details into a user’s calendar.
They are ideal for streamlining the promotion of events in emails, websites, and social media, enhancing engagement and ensuring attendees don’t miss important dates.
These tools are designed to cater to diverse needs, from personal event planning to professional event promotion, ensuring your attendees can easily add events to their preferred calendar.
Cal.et is a versatile and user-friendly tool that allows you to create “Add to Calendar” links for seamless event scheduling and promotion.
Why bridging the gap between PR and SEO is the only way forward for PR Profes...Isa Lavs
The lines between PR and SEO are blurring. SEOs are increasingly winning PR briefs by leveraging data and content to secure high-value placements. In this presentation, I explore the merging of PR and SEO, highlighting why SEO specialists are increasingly taking ‘PR’ business. I uncover the hidden SEO potential using PR tactics and discuss how to identify missed opportunities. I'll also offer insights into strategies for converting PR initiatives into successful link-building campaigns.
We’ve entered a new era in digital. Search and AI are colliding, in more ways than one. And they all have major implications for marketers.
• SEOs now use AI to optimize content.
• Google now uses AI to generate answers.
• Users are skipping search completely. They can now use AI to get answers. So AI has changed everything …or maybe not. Our audience hasn’t changed. Their information needs haven’t changed. Their perception of quality hasn’t changed. In reality, the most important things haven’t changed at all. In this session, you’ll learn the impact of AI. And you’ll learn ways that AI can make us better at the classic challenges: getting discovered, connecting through content and staying top of mind with the people who matter most. We’ll use timely tools to rebuild timeless foundations. We’ll do better basics, but with the most advanced techniques. Andy will share a set of frameworks, prompts and techniques for better digital basics, using the latest tools of today. And in the end, Andy will consider - in a brief glimpse - what might be the biggest change of all, and how to expand your footprint in the new digital landscape.
Key Takeaways:
How to use AI to optimize your content
How to find topics that algorithms love
How to get AI to mention your content and your brand
Compitive analysis on Noise pvt Ltd.pptxSauravDey45
ChatGPT
Competitive Analysis: Noise Smartwatch
Overview
Noise is an Indian electronics brand that primarily manufactures smartwatches, wireless earphones, and other electronic accessories. Noise smartwatches have gained significant popularity due to their affordable pricing, feature-rich offerings, and stylish designs. The competitive landscape for Noise smartwatches includes both local and international brands that cater to various market segments. This analysis will focus on key competitors, market positioning, product features, pricing strategies, and consumer preferences.
Key Competitors
Amazfit (Huami):
Strengths: Known for excellent battery life, robust fitness tracking, and premium build quality.
Weaknesses: Slightly higher price points compared to Noise.
Products: Amazfit Bip U, Amazfit GTS series.
Realme:
Strengths: Strong brand presence, integration with Realme smartphones, and aggressive pricing.
Weaknesses: Limited variety in smartwatch models.
Products: Realme Watch, Realme Watch S.
Boat:
Strengths: Competitive pricing, appealing designs, and extensive marketing.
Weaknesses: Relatively new to the smartwatch market, which may affect consumer trust.
Products: Boat Storm, Boat Flash.
Samsung:
Strengths: High brand credibility, advanced features, and premium design.
Weaknesses: Higher price points make it less accessible to budget-conscious consumers.
Products: Galaxy Watch Active 2, Galaxy Watch 3.
Xiaomi:
Strengths: Strong ecosystem integration, affordable pricing, and extensive features.
Weaknesses: Less focus on premium design compared to some competitors.
Products: Mi Band series, Mi Watch.
Market Positioning
Noise positions itself as an affordable yet feature-rich alternative in the smartwatch market. Its target demographic includes budget-conscious consumers and fitness enthusiasts who seek value for money without compromising on essential features like fitness tracking, notifications, and battery life. Noise leverages its strong online presence and partnerships with e-commerce platforms to reach its audience effectively.
Product Features Comparison
Noise Smartwatches:
Key Features: Heart rate monitoring, SpO2 tracking, multiple sports modes, customizable watch faces, notifications, and music control.
Battery Life: Typically lasts 7-10 days on a single charge.
Build Quality: Focus on lightweight and comfortable designs with water-resistant capabilities.
Amazfit Smartwatches:
Key Features: Advanced fitness tracking, GPS, AMOLED displays, and long battery life (up to 20 days).
Battery Life: 10-20 days depending on the model.
Build Quality: Premium materials and durable designs.
Realme Smartwatches:
Key Features: Basic fitness tracking, SpO2 monitoring, and notifications.
Battery Life: Up to 9 days.
Build Quality: Sleek designs but slightly limited in variety.
Boat Smartwatches:
Key Features: Heart rate monitoring, multiple sports modes, and customizable watch faces.
Title: Making Money the Easy Way: A Quick Guide to Generating IncomeWilliamZinsmeister
Welcome to "Making Money the Easy Way: A Quick Guide to Generating Income." This book is designed to provide you with practical, actionable strategies to generate income with minimal effort. Whether you’re looking to supplement your current income or create a full-time revenue stream, this guide covers a variety of methods to help you achieve your financial goals. We will explore opportunities available online, various investment strategies, profitable side hustles, creative approaches, and essential financial tips to ensure sustainable income growth.
How to Generate Add to Calendar Link using Cal.etY
Cal.et is a free tool that helps you create “Add to Calendar” links for your events. It supports popular calendar platforms like Google, Apple, Outlook, Yahoo, and Office365. Users can generate short, shareable URLs, customize event details, and even create QR codes for easy access. It’s ideal for embedding event links in emails, websites, and social media, making it easier for participants to save event information directly to their calendars.
If you’re at all interested in digital
marketing and in making a name for
your brand online, then it is crucial that
you understand how to properly make
use of content marketing. Content
marketing is currently one of the
biggest trends in digital marketing as a
whole and is an area that many website owners and brands are investing in
heavily right now thanks to the impressive returns that they are seeing.
Embark on style journeys Indian clothing store denver guide.pptxOmnama Fashions
Finding the perfect "Indian Clothing Store Denver" is essential for those seeking vibrant, authentic, and culturally rich attire in the heart of Colorado. Denver, a city known for its diverse culture and eclectic fashion scene, offers a variety of options for those in search of traditional and contemporary Indian clothing. Whether you're preparing for a wedding, festival, or cultural event, or simply wish to incorporate the elegance and beauty of Indian fashion into your wardrobe, discovering the right store can make all the difference.
3 must-know analytics techniques for data-savvy marketers
1. 3 of the best analytics
techniques for
data-savvy marketers
Discover how you can leverage data
analytics to understand your customers
better and drive more favourable outcomes.
apteco.com
3. As the resident problem-solver,
you’ve been tasked with making
sense of the crime scene.
apteco.com
3
3 of the best analytics techniques for data-savvy marketers
4. That crime scene is the vast landscape
of customer data, and working out what
it all means is not always easy,
apteco.com
4
3 of the best analytics techniques for data-savvy marketers
5. You may already have some clues.
For example, your customer churn rate
is strangely higher than you expected.
apteco.com
5
3 of the best analytics techniques for data-savvy marketers
6. So you ask yourself:
How do you recognise customers
who are most likely to lapse?
apteco.com
6
3 of the best analytics techniques for data-savvy marketers
7. The answer is hidden
in plain sight.
You just need to know how and where to look.
apteco.com
7
3 of the best analytics techniques for data-savvy marketers
8. You need data
analytics tools to
expose any hidden
truths and unravel the
marketing mystery
apteco.com
8
3 of the best analytics techniques for data-savvy marketers
9. Gain an in-depth
understanding of
your customers
apteco.com
9
3 of the best analytics techniques for data-savvy marketers
10. Gain an in-depth
understanding of
your customers
Make more
effective decisions
apteco.com
10
3 of the best analytics techniques for data-savvy marketers
11. Gain an in-depth
understanding of
your customers
Make more
effective decisions
Drive more
favourable outcomes
(higher conversion
rates, engagement,
etc.)
apteco.com
11
3 of the best analytics techniques for data-savvy marketers
12. Here are three techniques
you should know about
– and how to get started.
apteco.com
12
3 of the best analytics techniques for data-savvy marketers
14. Objective
Better understand the
factors involved in customer
decision-making, so you
can better predict what
they’re most likely to do in
the future.
apteco.com
14
3 of the best analytics techniques for data-savvy marketers
15. Questions you may ask:
What is my customer’s typical journey?
Are my predictions upheld when tested against known behaviours?
How do I reach my customers and prospects?
• How many interactions do they have before they purchase?
• Does it matter how long it has been since their previous
purchase?
• Are there combinations of products customers are more
likely to purchase?
apteco.com
15
3 of the best analytics techniques for data-savvy marketers
16. How to get started:
• Identify behavioural features within your past data. This can be split into
three categories:
1. Summary measures (simple metrics such as average spend and basket
abandonment rate)
2. Dynamic trends (such as a reduction in web visits or an increased
average linger time)
3. Sequence of events (a combination of factors that lead up to a
behavioural outcome)
• Lookout for these patterns in your customers’ current behaviour
• Predict their next steps by assigning a score to people based on what they
are doing now
apteco.com
16
3 of the best analytics techniques for data-savvy marketers
17. Look for a tool that offers:
apteco.com
17
3 of the best analytics techniques for data-savvy marketers
18. The ability to run the
model on multiple
historical dates
for evaluation and
application
Look for a tool that offers:
apteco.com
18
3 of the best analytics techniques for data-savvy marketers
19. The ability to run the
model on multiple
historical dates
for evaluation and
application
Options for fixed
point-in-time
modelling or event-
driven modelling
Look for a tool that offers:
apteco.com
19
3 of the best analytics techniques for data-savvy marketers
20. The ability to run the
model on multiple
historical dates
for evaluation and
application
Options for fixed
point-in-time
modelling or event-
driven modelling
Integration with
programming
languages such as
Python and R for
advanced analysis
techniques
Look for a tool that offers:
apteco.com
20
3 of the best analytics techniques for data-savvy marketers
21. Segmentation
apteco.com
21
3 of the best analytics techniques for data-savvy marketers
apteco.com
21
3 of the best analytics techniques for data-savvy marketers
22. Objective
Make your customer base
easier to manage by placing
customers into meaningful
groups that share common
characteristics.
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23. Questions you may ask:
How do my customers move within marketing segments over time?
How good is my business at retaining customers?
How can I increase engagement and my campaign response rates?
When are customers most likely to lapse?
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3 of the best analytics techniques for data-savvy marketers
24. How to get started:
• Build segments that are meaningful to your organisation
using demographic, location, psychographic or behavioural
variables
• Choose to examine your customers based on a fixed point in
time or a reference point that is specific to the individual
• Run and review your segmentation reports
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3 of the best analytics techniques for data-savvy marketers
25. Look for a tool that offers:
apteco.com
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3 of the best analytics techniques for data-savvy marketers
26. The ability to
examine customer
segments at a point
in time and how they
evolve over time
Look for a tool that offers:
apteco.com
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3 of the best analytics techniques for data-savvy marketers
27. The ability to
examine customer
segments at a point
in time and how they
evolve over time
Built-in segmentation
reports such as
migration, journeys,
and retention reports
Look for a tool that offers:
apteco.com
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3 of the best analytics techniques for data-savvy marketers
28. The ability to
examine customer
segments at a point
in time and how they
evolve over time
Built-in segmentation
reports such as
migration, journeys,
and retention reports
Seamless data
export options for
swift execution in
digital and offline
marketing channels
Look for a tool that offers:
apteco.com
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3 of the best analytics techniques for data-savvy marketers
29. Best Next
Offer
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3 of the best analytics techniques for data-savvy marketers
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3 of the best analytics techniques for data-savvy marketers
30. Objective
Boost conversions and
engagement by customising
your messaging and offer
to include relevant product
recommendations.
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3 of the best analytics techniques for data-savvy marketers
31. Questions you may ask:
What products can I cross and
upsell to my existing customers?
How can I identify customers’
wishes before they arise?
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3 of the best analytics techniques for data-savvy marketers
32. How to get started:
• Access your customer transaction history
• Apply popularity and propensity weightings to determine which
product combinations are most popular, and what tendencies
individual customers demonstrate
• Your data analytics solution will crunch through the data for you,
showing you associations between your products, services and
what is commonly bought together
• Save ‘Best Next Offer’ as a variable for creating audience selections
• Take into account additional aspects such as seasonal effects,
current inventory levels, and profit margin
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3 of the best analytics techniques for data-savvy marketers
33. Look for a tool that offers:
apteco.com
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3 of the best analytics techniques for data-savvy marketers
34. Built-in AI, wizards and
machine learning
Look for a tool that offers:
apteco.com
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3 of the best analytics techniques for data-savvy marketers
35. Built-in AI, wizards and
machine learning
Advanced predictive
modelling techniques
Look for a tool that offers:
apteco.com
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3 of the best analytics techniques for data-savvy marketers
36. Want to learn more?
Download our free eGuide to get seven bonus
techniques you should have in your toolkit.
Download eGuide