Community Member Spotlight
Community Member Spotlight
Building Confidence and Community: Our Experience with She Loves Data
In today’s tech industry, women often face unique challenges. At “She Loves Data,” we empower women through community, mentorship, and skill-building. In this post, we feature an interview with two of our community members, Khad Sanari, Analyst and Shad Sanari, Project Manager, who share how our programs have transformed their confidence and career paths. Discover their inspiring journeys and the impact of “She Loves Data” on their professional growth.
Interview with Khad and Shad Sanari, Community Members based in Singapore
We are Khad and Shad, a pair of identical twin sisters from Singapore. After establishing our careers in the financial services industry, we made a significant pivot into the world of data analytics. Recently we embarkedembark upon a short career break to enhance our technical skills whilst taking the opportunity to travel to some of the most exciting places.
As avid photographers and video editors during our downtime, we find creative expression in capturing and crafting visual stories from our travel adventures and sharing it with our close friends and family. Outside of our work, we like to keep active by playing netball once a week.
Through our story, we aim to inspire women who have stepped away from traditional corporate careers, regardless of the reasons for their decisions. Our journey demonstrates that one should never be afraid to return and pursue meaningful work that aligns with their evolving aspirations and values.”
Q1) How did you first hear about She Loves Data?
We learned about SLD through an event, “The Impact of a Mentoring Culture,” held at the Visa Singapore office last October 2023. The event also marked SLD’s 7th anniversary. Since then, we have followed SLD on a professional networking platform to ensure we are kept abreast of any events which can participate in and expand our network.
Q2) What motivated you to start participating in our programs/events?
As women pursuing a career in data analytics, we were eager to get more involved in the local tech community. We had heard great things about the SLD initiative and were excited by the opportunity to connect with other women who shared similar interests. Our primary motivation is to enhance our skills, expand our professional network, and gain insights from more experienced practitioners.
Q3) Can you describe your experience with these programs?
Our experience with the SLD programs has been incredibly valuable. The workshops and events have provided us with a supportive, collaborative environment to learn new data analysis techniques, deepen our understanding of emerging technologies, and sharpen our presentation skills. We have especially enjoyed the panel sessions, where we have been able to receive advice from women who have successful data careers. It’s been empowering to be part of a community that celebrates and uplifts women in data.
Q4) What were some of the most valuable skills or knowledge you gained from our workshops?
The workshops we have attended have really helped strengthen our understanding of data as a critical asset in the modern digital landscape. It is a powerful tool to drive business decisions and improve operations.
It also provided us with a solid foundation in the core concepts, tools, and best practices essential for building and maintaining robust data engineering systems. These skills would be valuable for a career in data engineering or for anyone working with data in an organizational context.
Q5) How have the skills and knowledge you gained from SLD influenced your career?
Participating in the SLD programs has had a direct, positive impact on our career trajectory. The technical skills that we have gained will allow us to tackle more complex projects at work. But just as importantly, the confidence and sense of community we have gained have inspired us to be more proactive about taking on leadership roles and new challenges. We feel better equipped to navigate the male-dominated tech industry as women.
Q6) Have you noticed any changes in your confidence or approach to work since completing our programs? Did SLD help you address any specific obstacles or barriers in your career?
Before getting involved, we sometimes struggled with imposter syndrome and would hesitate to speak up in meetings or social settings. Now, we feel much more self-assured in our abilities in public speaking. We are more willing to voice our ideas, knowing that we have a strong support network behind us. The programs have profoundly impacted our level of confidence. The network of women we’ve connected with has provided us with mentors, collaborators, and cheerleaders. We can reach out to other members for advice, job leads, or moral support when facing challenges. We’ve gained a profound sense of belonging and camaraderie that makes us feel empowered as a woman in tech.
Q7) How important do you think networking and community are for women in data-related fields?
We firmly believe that networking and community are essential for women in data-related fields. The tech industry can still be quite male-dominated and insular, so having a strong support system of other women is critical. Networking helps us discover job openings, business partnerships, and mentorship opportunities. Being part of a community provides a sense of belonging, validation, and accountability.
Q8) Have you made any lasting connections or friendships through our program?
It’s early days yet as the program is usually online but through the in-person event we are always excited to meet Jana in person. She has been absolutely warm and authentic towards us. We never miss capturing a group photo or a selfie every time we meet!
Jana Marle-Zizkova (Co-Founder She Loves Data) with Khad and Shad at event in Singapore – The AI Mindset: How to Prepare for an AI-Fueled Future, May 2024
Q9) What are your future goals and aspirations in the field of data?
Our long-term goal is to continue growing as a data leader and innovator, driving positive change within our organization and the broader industry. We aspire to one day take on a leadership or management role. We are passionate about using data to address social and environmental challenges. We’d love to explore opportunities to apply our data science skills towards improving the environment and climate-related issues.
Q10) What advice would you give to someone considering joining SLD?
Our advice to anyone considering joining the SLD community would be to take the leap and get involved! These programs offer an unparalleled opportunity to build both your technical skills and your professional confidence as a woman in data. Even if you’re just starting out in your career, we encourage you to participate with an open mind and a willingness to learn. Beyond the skills development, being part of this supportive community can be truly transformative. You’ll gain a sense of belonging, camaraderie, and empowerment that will serve you well throughout your data journey.
Q11) Do you have any closing thoughts or messages for the She Loves Data community or to the organizers and volunteers who make these programs possible?
We’d like to take this opportunity to express our heartfelt gratitude to the SLD community and the incredible volunteers who make these programs possible. Your tireless efforts to create such a welcoming, empowering, and enriching space for women in data have had a profound impact on our professional and personal growth. The knowledge, skills, and confidence we’ve gained through our involvement have been invaluable. What we value most is the sense of belonging and sisterhood that SLD has fostered. The camaraderie, mentorship, and mutual support we’ve experienced have been truly transformative.
To the organizers and volunteers – your passion, dedication, and vision for empowering women in data are truly inspirational. Your work is making a real difference in the lives of so many.
Volunteer Spotlight
Driving Change Through Data: Alena’s Journey with She Loves Data in Dubai
In our latest Volunteer Spotlight, we delve into the inspiring story of Alena Placha, the lead of She Loves Data’s Dubai Chapter. Alena’s journey with She Loves Data began when she embraced the challenge of rejuvenating the Dubai chapter, a task that involved building the chapter from the ground up in a region new to her. This interview reveals not only the personal and professional transformations Alena has experienced through her involvement with She Loves Data but also highlights the broader impact of the organization on fostering data literacy and community engagement in the Middle East.
Interview with Alena Placha, the She Loves Data Dubai Chapter Lead
Q1: What motivated you to join She Loves Data as a volunteer, and how do you think your values align with the mission of the organization?
I was planning to move to Dubai, so when Jana (Co-Founder of She Loves Data) offered me the opportunity to restart the chapter there, I was incredibly happy and honored. I felt a great sense of responsibility in restarting the activities of SLD in a region that was entirely new to me, essentially starting from scratch. We had lost touch with the community over the years, so I had to start from the very beginning.
Q2: In what way/role have you been associated with SLD? Has your role changed, if so why and how?
I was asked to join as a Chapter lead right from the beginning, and I am still in that position.
Q3: Please share how SLD has impacted your life: a) personally and b) professionally?
I don’t know where to start. As I mentioned, I came to Dubai alone. The mission I took on with restarting SLD ME not only helped me build my professional network but also helped me find people who have now become more than just ‘work’ contacts. We have developed deeper connections and relationships because we aim for the same cause. Whether it’s overrated or not, doing good and helping others really connects people and brings them together. Having a positive impact on the people around you and society is so fulfilling and keeps me going. There are many inspirational stories here in the Middle East that need to be heard, and I believe SLD can provide the platform to do that.
So far, the feedback on SLD activities here has been amazing, and we are only at the beginning. The partnerships we have managed to create here are wonderful, and now I am facing a situation where we have so many plans but not enough people on the team. Fortunately, the team is already growing rapidly, and I know in my heart that this will accelerate even further.
Q4: Was there any challenge you encountered while volunteering with She Loves Data and how you or the team overcame it?
Yes, the biggest challenge was that we were completely unknown in the region, and I was here alone. I talked about SLD with literally everyone I met, telling them about the organization, what we have been doing for the past years, and encouraging them to join the community and work together. There are many women-focused initiatives in the region, so I had to create the right pitch to articulate what makes us different. But honestly, it was easier than I thought because SLD has done really amazing and impactful things, so it was ‘easy to sell’.
Q5: In your view, what has been the most significant impact of She Loves Data on the local or global community?
For me, the most significant impact is that we have a real, tangible, and measurable impact. This is something that sets us apart from other organizations in the region. Since we work with data, we know our community very well. We are bringing people together and offering free education, which is so underestimated and so important.
When I saw our signature programs, I was amazed. The curriculum is so well thought through that I felt like putting the creators on a pedestal because there is so much work, effort, and hours behind it.
In addition, I am honestly overwhelmed by the fact that people in SLD do this because they genuinely want to help others. The whole organization is volunteer-based; we don’t ask for any membership fee or premium subscription. It is free and for everyone. I feel that in today’s world, there are fewer and fewer things that are simply given for free with nothing but kindness and good intention.
Q6: Where do you see the role of She Loves Data in the future of data literacy and inclusion? How do you envision your continuing involvement?
I see there is enormous potential. We have already reached 17 different regions in the world, and I really hope we will continue to grow because I strongly believe that what we do could be incredibly beneficial to many regions where the impact would be unbelievable. For example, LATAM or Africa. The world is not just divided between the rich and the poor but also between the educated and uneducated, and the data literate and illiterate. If you look at the activities of UNDP and their World Data Forum program for sustainable development, the direction is clear.
Community Spotlight: Empowering Women in Data Through the UK & Ireland Chapter of She Loves Data
Discover how the UK & Ireland Chapter of She Loves Data is making strides in the tech world. Learn about their impactful events, community outreach, and how you can get involved in promoting inclusivity in data and technology fields.
How does Aishwarya Ramakrishnan empower Women in Data Science?
Discover Aish Ramakrishnan’s journey with She Loves Data, how volunteerism has shaped her mission to empower women in data science, and her recognition as a top tech leader.
Master Python Programming for a Thriving Tech Career
Python has emerged as a leading programming language, recognized for its remarkable versatility and beginner-friendly nature. This dynamic language finds application in diverse fields, including web development, task automation, design, AI and machine learning, data engineering and data analysis. With its open-source nature and a vibrant online community, Python is the go-to choice for beginners in web development, offering flexibility and simplicity. In this article, we explore the reasons behind Python’s immense popularity, its relevance in today’s tech landscape, and the vast array of growth opportunities it presents.
What is Python?
Python is an open-source, high-level, general-purpose programming language that has captured the hearts of many developers and learners worldwide. It’s characterized by its thriving online community and a vast array of applications, making it an ideal choice for beginners in the web development field.
Python stands out for its readability and simplicity, enabling developers to tackle complex tasks with ease. This interpreted, interactive, and object-oriented language also boasts features like modules, dynamic typing, dynamic data types, and classes, which improves its versatility. Additionally, Python’s portability, extensibility, and ease of coding contribute to its popularity.
One of Python’s key strengths lies in its focus on user experience and usability, making it a favorite in numerous industries and organizations. It can seamlessly integrate with other languages like C, C++, Spark and SQL to tackle more demanding tasks. In recent years, Databricks has leveraged the integration of Spark, Python, and SQL on their service, becoming a major lakehouse platform for Data Engineering and Machine Learning. Data scientists utilize Python for data analysis, engineers for software development, and web developers for crafting the backend of websites.
Benefits Python Brings
Python offers many benefits that can significantly impact career opportunities and professional growth. One of the advantages of learning Python is its industry relevance and demand. With Python’s growing importance across multiple sectors, such as AI, machine learning, web development, and the Internet of Things (IoT), mastering this versatile language can significantly improve employability, enabling professionals to explore diverse career paths and excel in their respective fields. Additionally, Python’s usage spans fields like finance, scientific computing, security, and game development, allowing professionals to choose a domain that aligns with their interests or career aspirations.
The language’s adaptability and extensive range of libraries make it a preferred choice for various industries, providing opportunities for software developers, data scientists, and freelancers. Python is probably the easiest coding language to learn and work with due to its popularity. The Internet is full of free educational content and the programming community is always willing to help with debugging and improving the code. Most of the problems have been well documented and answered thoroughly. Python’s flexibility allows individuals to engage in various roles, from creating desktop and mobile applications to automating routine processes, leading to diverse income streams and potential entrepreneurial ventures.
Furthermore, with Python’s prominence in the global job market and its recognition as the most popular language, learners gain access to an expansive community of support and collaboration, adding immeasurable value to their learning journey and professional networking. Ultimately, mastering Python equips individuals with skills in high demand in the job market, offering competitive salaries and diverse career pathways.
Career Paths Utilizing Python Skills
Python opens doors to a multitude of careers across various industries, such as:
Python Developer: Responsible for building and testing server-side web applications in Python, handling scalable code, and collaborating with front-end developers to integrate user-facing elements.
Data Analyst: Focuses on working with large datasets, utilizing Python’s libraries such as NumPy, Pandas, and Scikit-learn for data manipulation, analysis, and visualization. Often involved in developing predictive models using machine learning tools like TensorFlow and Keras.
Product Manager: Involved in market research, identifying new features, and supporting product development using data insights. A profound understanding of Python can be crucial for analyzing market trends and consumer needs.
Machine Learning Engineer: Constructs and trains machine learning models for applications such as natural language processing and computer vision. The role demands expertise in Python for model development and analysis.
Principal Software Engineer: Leads and oversees a team of developers using Python for coding, testing, and documentation in software projects.
Senior Data Scientist: Manages teams, focusing on Python for natural language processing and sentiment analysis, providing insights to solve complex business problems.
Senior Software Engineer: Utilizes Python not only for software development but also for data analysis, web scraping, and automation. They play a critical role in developing new tools and products.
Software Development Engineer: Designing computer programs, employing Python for analytics, data collection, and various other aspects of software creation.
DevOps Engineer: Central to automation tasks, using Python for continuous integration and delivery processes, and ensuring smooth workflow within a team.
Data Engineer: Implements Python to enhance data access, security, quality, and maintenance, collecting and arranging data from multiple sources for machine-readable usage.
System Engineer: Analyzes computer systems and designs solutions to enhance technical infrastructure, supporting and updating systems where necessary.
Mechanical Engineer: Utilizes Python for data analysis and automation, facilitating quick solutions to complex numerical problems and aiding in testing new designs.
Web Developer: Both front-end and backend developers use Python for creating the architecture and inner workings of websites, writing and debugging code for a seamless user experience.
Database Administrator: Focuses on database administration and management using Python, which is essential for maintaining and administering organizational databases.
Cyber Security Expert: Utilizes Python to assess and defend against online threats, building models for natural language processing and other AI applications. Python is pivotal in automating software testing and deployment for cybersecurity purposes.
Establishing a Career in Python
Becoming a proficient Python developer involves mastering the language’s fundamental concepts, including data types, control structures, and functions. Proficiency in software development principles such as design patterns and object-oriented programming is crucial. Furthermore, familiarity with well-known libraries and frameworks is essential for web development and data analysis. Adeptness with databases, SQL, version control systems and debugging techniques is also necessary. Python developers should possess problem-solving capabilities, adapt to evolving technologies, and remain updated on industry trends and best practices.
The journey to launching a career in Python involves various routes. Obtaining foundational Python knowledge can commence through a computer science degree, coding bootcamps, or self-study using online resources, tutorials, and forums. Learning other programming languages alongside Python, such as JavaScript and Ruby, can improve a developer’s skill set, mainly as multiple languages are often utilized in creating a single web page or program. Attending a coding bootcamp offers a fast-track to obtaining a Python certificate, accompanied by access to job services aiding in industry connections and interview preparation. For those aiming for advanced roles, pursuing a degree in computer science may be advantageous, especially as certain employers still prioritize candidates with formal degrees. Building a robust portfolio showcasing successful projects is pivotal in setting oneself apart, eventually paving the way to secure desirable job opportunities in the field.
Ultimately, becoming a sought-after Python developer requires continuous learning, practical application, and a diversified skill set beyond technical expertise. Through a structured approach, mastering the foundational skills, advancing domain-specific knowledge, and continuous adaptation to emerging trends and technologies, aspiring Python developers can set themselves on the path to success in the thriving tech industry.
Master Python Programming for Flourishing Tech Career
Are you eager to explore the dynamic world of Python programming? She Loves Data offers an extensive curriculum covering Python programming’s foundational concepts alongside in-depth insights into data analytics, machine learning, data visualization, web scraping, and natural language processing. By enrolling, you’ll gain mastery over crucial Python elements, such as data types, lists, dictionaries, basic operators, and functions. This comprehensive course covers indispensable topics, including R, Python programming, machine learning algorithms, NLP concepts, and data visualization through interactive learning models. Upon completion, you not only equip yourself for a prosperous Python-centric career but also earn a prestigious certificate of accomplishment. Enroll now and set your sights on a promising future in the tech industry!
She Loves Data and The Martech Weekly Collaborate
She Loves Data and The Martech Weekly Collaborate to Enable Women in Digital Marketing Amidst the Digital Revolution
(Singapore, July 2023) She Loves Data (SLD), a global organization with more than 25,000 members, dedicated to helping women enter and excel in the data and digital industries, has joined forces with The Martech Weekly (TMW), an industry-leading global media and research company, to drive positive change, foster diversity, and address the increasing demand for talent in the rapidly evolving digital marketing landscape.
The digital revolution has led to an explosion of marketing technologies, transforming the way businesses engage with customers. According to Chiefmartec.com, the 2023 marketing technology landscape supergraphic showcases 11,038 solutions. This is nearly twice the 6,829 solutions it reported in 2018, demonstrating the industry’s growth and complexity.
Recognizing this demand for talent, She Loves Data is committed to enabling women in data and digital marketing, by continuing to provide its popular upskilling certificate courses for free, in addition to other programs like mentoring, networking and provision of job opportunities at top martech and data companies. Studies show that gender diversity in the workforce leads to better business performance and innovation. According to McKinsey & Company, companies with diverse executive teams are 33% more likely to outperform their peers.
To support this mission, The Martech Weekly, represented by Juan Mendoza, Founder and Editor-in-Chief, will contribute a significant portion of proceeds from their inaugural TMW 100 Martech Innovators Awards to She Loves Data’s initiatives. This contribution will help support the talent gap by providing women access to SLD’s mentorship programs, educational workshops and scholarships.
The TMW 100 Awards aims to bring clarity to the marketing technology industry by ranking the most innovative marketing technology companies from 1st to 100th place globally. Applications are open until 25 August 2023 and the winners will be announced at the MOps-Apalooza live event in Anaheim California on 27 November 2023.
“We are thrilled to collaborate with The Martech Weekly to empower women further in the data and digital marketing fields,” said Jana Marle Zizkova, Co-founder and CEO of She Loves Data. “As the industry continues to evolve, it is vital to have diverse talent driving innovation. By providing resources and opportunities, we can equip women with the skills necessary to thrive in this dynamic landscape.”
According to a study by Women in Marketing Technology, women only occupy 26% of marketing technology leadership roles, despite studies that underline the importance of diversity in the martech space.
“Our collaboration with She Loves Data aligns with our commitment to celebrating innovation and promoting diversity in martech,” said Juan Mendoza. “The digital marketing landscape thrives on fresh ideas and diverse talent. By supporting She Loves Data’s initiatives, we contribute to narrowing the gender gap, and fostering a more vibrant and innovative industry.”
Martech providers and the companies that use their platforms can support by participating in the TMW 100 Awards, the world’s first independent awards platform that champions innovation in the global martech industry.
For more information about The Martech Weekly and the TMW 100 Awards, please visit: https://www.themartechweekly.com/tmw100/ .
Optimizing Marketing Channels with Marketing Data and Analytics
In the fast-paced realm of digital marketing, data holds the key to unlocking success. And it is essential to develop expertise in measuring marketing channels, encompassing web and social media analytics, email analytics, mobile analytics, and more. By sharpening measurement skills and understanding how to optimize marketing channels, organizations can navigate the ever-changing digital marketing landscape with confidence and drive tangible results for their marketing initiatives. In this article, we offer insights into the measurement and optimization of marketing channels, drawing on the expertise of Gabriel Nani dos Santos, MarTech Solutions Director at Kinesso. Gabriel is also one of the trainers in the SLDxDigital certification program, which equips individuals with the competencies needed to thrive in the digital landscape.
The Meaning and Importance of Marketing Optimization
Marketing optimization refers to the process of improving the effectiveness of marketing efforts to achieve better results.
In essence, marketing optimization focuses on achieving marketing and overall business objectives. To accomplish better outcomes, organizations and marketers have access to a range of marketing tools and tactics. These outcomes can be measured in terms of clicks, impressions, sales, or other desired actions, and should align with the marketing strategy.
Some common marketing channels include the following:
- Social Media
- Email Marketing
- Content Marketing (blogs, websites)
- SMS Marketing
- Search Engine Optimization (SEO) (organic and paid search)
- Direct marketing
- Public Relations Campaigns or Event Marketing
“By optimizing marketing channels, organizations will better understand their marketing channel mix and which channels perform better for which campaign. This insight can help organizations to increase return of investment (ROI), increase their competitive advantage, reduce cost, and create scalability for growth.”, says Gabriel Nani dos Santos, MarTech Solutions Director at Kinesso.
Optimizing marketing efforts begins by gaining a comprehensive understanding of the target audience. This involves researching demographic information, preferred payment methods, purchased products or services, competitor strategies, social media usage patterns, and platform preferences. These insights help in identifying buying habits and preferences.
Moreover, to understand the effectiveness of marketing campaigns, it is crucial to establish measurable and relevant performance indicators. Without this step, the marketing strategy cannot be optimized for success. Identifying the right Key Performance Indicators (KPIs) and measuring them accurately is essential. This enables businesses to determine which marketing investments provide the highest value and identify areas that require optimization. Employing appropriate marketing analytics is the most effective way to gain this understanding.
Before selecting a marketing channel for launching a campaign, organizations should consider the following steps, as recommended by Gabriel:
- Review the existing target audience
- Confirm the marketing KPIs
- Allocate the budget appropriately
- Conduct industry research and stay updated on trends
- Test existing channels and gather insights into their current performance
These steps help organizations make informed decisions about the marketing channels to utilize, ensuring efficient allocation of resources and maximizing campaign effectiveness.
Determining Important Marketing Data and Analytics
The effective utilization of marketing analytics is essential for a comprehensive marketing strategy. Analytics involves identifying patterns within the data to fine-tune efforts and achieve objectives.
“Organizations can effectively measure the performance of marketing channels by aligning on a marketing KPI framework across all channels and use tools to help with analytics and insights generation,” adds Gabriel
To effectively measure the impact of a marketing channel, it is crucial to collect relevant data. Marketing data serves as a reflection of the performance of marketing tools and techniques. While the specific data points depend on the channel being measured, it is generally recommended to capture customer behavior, engagement, interactions, budget allocation, and revenue whenever applicable.
There are user-friendly tools to automate the collection of these data points, allowing more time for optimization. Automation enables organizations and marketers to:
- Gather data on the success of marketing efforts
- Schedule the launch of marketing campaigns
- Manage the timing of social media marketing activities
- Identify and eliminate underperforming ads
- Automate email communication
- Streamline the customer journey
- Provide recommendations for optimizations
- Implement retargeting strategies
As campaigns are tracked, valuable data on their performance can be extracted. Now, the crucial step is to transform this data into actionable insights that guide future business decisions. Equipped with in-depth insights about customers and the performance of various posts and campaigns, organizations can effectively adjust and optimize future marketing efforts.
“There is a wide variety of tools that can help marketers to analyze the performance of their marketing channels. These tools will vary based on the channels they are reporting on, what data can be ingested, and which insights can be generated.”, says Gabriel.
Therefore to understand the impact of each marketing channel, data-driven marketers should closely monitor these insights. This enables businesses to derive meaningful and comparable insights over time. Developing this skill may require some time and constant experimentation.
The final step in the optimization process is, reporting these findings and gleaning insights in order to r track the performance of each marketing channel effectively. Once relevant insights and marketing analytics have been identified, it is crucial to present them clearly. Regular marketing analytics reports should be conducted to enable comparisons, track changes in performance and to get a more accurate understanding of how each marketing channel impacts the KPIs.
Challenges and Best Practices When Optimizing Marketing Channels
The digital world is constantly changing, and marketers and organizations should adapt quickly. While optimizing marketing channels, they will likely encounter some limitations.
Some of the challenges to be aware of are the following:
- Lack of clarity around marketing KPIs which can lead to inconsistency in how optimization is implemented.
- Lack of technical understanding of the tools being used to analyse data and optimize channels.
- Limited budgets and resource constraints can make it challenging to invest appropriately in all channels or experiment with new strategies.
- Data Privacy regulations which can impose restrictions on collecting, processing, and using customer data.
- Resistance to process change that can happen from the implementation of optimization strategies.
A clear strategy and action in place can help to overcome these challenges. Gabriel suggests that organizations consider the following approaches:
- Foster a clear understanding of marketing KPIs and ensure alignment across the organization
- Develop internal skill sets and expertise to effectively analyze data and optimize marketing channels
- Stay informed about data privacy regulations and ensure compliance in data collection and usage
- Facilitate internal alignment with stakeholders to manage resistance to process change.
Another important approach is to effectively communicate technical concepts to non-technical stakeholders and marketers when discussing optimizing marketing channels.
“Start with why marketing optimization is important and clearly articulate the potential impact on key business metrics such as ROI, customer acquisition, revenue growth, etc. Then, bring it down to the framework (best practices) that needs to be implemented to effectively generate business outcomes. Use visual aids to present data in a visually appealing way that is easy-to-understand. Finally, highlight the roles and responsibilities that will be expected from each stakeholder. No one needs to be across the entire process, but it is important to have a high-level understanding of the framework, so you know when you need to start your part before handing it over to another person.”, says Gabriel.
By following this approach, stakeholders will have a high-level of understanding of the framework, enabling effective collaboration and coordination throughout the optimization process.
Here are 5 steps that are part of the marketing measurement framework.
- What are you measuring and why
- Choosing the right method for analysis
- Collecting and questioning data
- Making the results meaningful
- Reporting it back
What is Next for Marketing Optimization
When developing marketing strategies and optimizing marketing channels, organizations should consider key trends from the marketing and technology industry. These trends include data privacy and customer expectations, which demand attention in martech strategies.
According to Gabriel, organizations should regularly assess and evaluate whether their KPIs and goals align with customer expectations and whether their strategies are future-proof in terms of user privacy regulations. As technologies evolve rapidly, being aware of these trends is crucial.
Whether organizations are focused on measuring and optimizing multi-channel or single-channel marketing strategies, it is essential to follow the marketing measurement framework. This framework provides a structured approach to effectively track and measure the performance of marketing initiatives.
Multi-channel marketing optimization
Today optimization plays a crucial role as customers interact with brands through multiple channels such as social media, websites, offline stores, emails, and resource downloads. While a channel optimization strategy can focus on a single channel, it’s increasingly important to develop comprehensive cross-channel or multichannel optimization strategies.
According to Gabriel Nani dos Santos, promoting your brand through a single channel is no longer sufficient for maximizing brand exposure. Successful digital strategies now involve using multiple channels to effectively reach the target audience. To measure the success of campaigns, it is essential to utilize the right technology that enables exploration of the best-performing channels.
“Technologies are evolving at a rapid pace, so marketers need to regularly assess and evaluate whether KPIs and goals are still meeting customer expectations and if the company is future proof for user privacy regulations,” adds Gabriel.
When measuring multi-channel marketing strategies, powerful tools can be employed to track and monitor channel performance. Google Analytics, for instance, is an excellent tool that offers a wealth of data for analysis. By optimizing across channels, leveraging appropriate technology, and employing multi-touch attribution methods, organizations can maximize their marketing impact and drive better results.
To delve deeper into these concepts and acquire the necessary skills and knowledge to thrive in the digital age, explore the SLDxDigital certification program. This program offers a curriculum designed to equip individuals with the expertise needed to optimize campaigns, analyze results, and make data-driven decisions. It covers various aspects, including mastering marketing channels and understanding the holistic customer journey.
Unveiling the Power of Digital Analytics
Unveiling the Power of Digital Analytics: Harnessing Data Insights for Business Success
In this digital age, data is everywhere, and businesses have an ocean of data to manage from their online activities. From their website’s dynamics to social media engagement, every click, like and share leaves a trail of valuable information for social media managers to dig through. This is where the power of digital analytics comes into play. Businesses are using this plethora of available data and making some ground-breaking decisions leading to their success.
In this article, we delve into the world of digital analytics and explore how it can revolutionize the way businesses operate and scale. Let’s first dig into the “What” of it.
What is Digital Analytics?
Digital Analytics is the process of collecting, measuring, analyzing and interpreting the data generated from your different online platforms and gleaning actionable insights to make statistical analysis and informed business decisions. The primary objective of digital analytics is to understand and optimize the performance of digital assets, such as websites or marketing campaigns, by leveraging data-driven insights. By examining data related to user engagement, traffic sources, conversion rates, and other key metrics, businesses can make informed decisions and improve their digital strategies. Gianna, our speaker for the upcoming class for “Foundation of Digital Analytics” explains digital analytics as “Measurement solutions and systems that quantify the impact of online activities (i.e. advertising campaigns, social campaigns, etc) on defined KPIs to evaluate performance against stated objectives and goals”.
Comparison of Data Analytics and Digital Analytics
Data analytics and digital analytics are closely related fields that both involve the analysis and interpretation of data. The difference between them is also quite subtle where in data analytics, we use different technological and big data analysis to analyze our trends and correlation and in digital analytics we analyze digital data from diverse sources including webapps and mobile apps. While data analytics improves the efficiency of information, digital analytics allows businesses to provide customized experiences for their potential customers.
“Data Analytics is focused on yielding useful insights and information from raw data sets to guide decision making and help businesses achieve their stated goals. Digital Analytics is a subset of Data Analytics, as the latter can include offline activities (such as Offline Media campaigns) in the context of marketing investments “, says Gianna.
Rita, another speaker of our upcoming class of “Foundation of Digital Analytics” compares the two as follows.
“Data Analytics and Digital Analytics are two distinct but interconnected fields that involve analyzing data to derive meaningful insights. While they share similarities, they differ in their focus and the types of data they analyze.
Data Analytics is a broader discipline that encompasses the analysis of data from various sources, both structured and unstructured. It involves extracting, cleaning, processing, and analyzing data to discover patterns, trends, and correlations. The objective is to uncover insights that can drive strategic decision-making, identify business opportunities, optimize processes, and solve complex problems across different industries.
Digital Analytics specifically deals with the analysis of data collected from digital channels. This includes data from websites, mobile apps, social media platforms, and online marketing campaigns. Digital Analytics focuses on measuring and analyzing user behaviour, engagement, conversions, and other digital-specific metrics.
Data Analytics focuses on analyzing data from various sources to gain insights across different domains, while Digital Analytics specifically analyzes data from digital channels to optimize digital strategies and improve online performance. With the rise of digital channels in marketing and business operations, there is an increasing need for data and marketing professionals to understand and master the skills of digital analytics.”
What are the fundamental components of Digital Analytics?
- According to Gianna, the following are the most fundamental components of digital analytics:
“Individuals who are fluent in the business context, goals and objectives to guide the organization and analysis of data.” Human intelligence and ideas without a doubt are pivotal components in organization of facts and decision making. - “Infrastructure for accurate and timely collection of relevant raw data”. This involves the usage of effective platforms and implementation of tracking mechanisms such as tags, cookies, tracking codes on websites, mobile apps, and other digital platforms. The data collected may include information about user interactions, behaviors, demographics, traffic sources, and more.
- “Tools to perform necessary analyses on raw data sets to generate useful insights and information”. This list of tools used for this purpose includes Matplotlib, Ggplot2, Seaborn, Sci-kit learn, and more.
- “Tools to connect and report insights and information across data sets to enable decision-making.” This includes a range of tools such as BI tools, Data visualization tools, SQL tools, Data integration tools, and more.
- Data-driven decision making as part of the organization’s culture.
What are some use cases and real-time applications of Digital Analytics?
We consulted Gianna, our speaker about her views on it and the following is her response.
- “Measure impact of brand campaigns on driving incremental brand awareness using Lift methodology.
- Measure impact of performance campaigns on driving incremental online purchases using Lift methodology and optimize campaign parameters accordingly.
- Quantify ROI of digital channels to guide marketing investment allocation.”
Rita, the second speaker of our program added a few more real-time use cases such as:
- “Digital Analytics on Meta allows businesses to track and analyze the performance of their advertising campaigns on the platform. It provides data on impressions, reach, click-through rates, conversions, and other relevant metrics. This enables businesses to assess the effectiveness of their ad campaigns, make data-driven decisions, and optimize their targeting, creative elements, and bidding strategies.
- Lift testing and A/B testing on Meta help businesses adopt a test-and-learn mindset to optimize their marketing spend using experiments and understand the true incremental impact of their digital activities.
- Holistic analytics methods such as Marketing Mix Modelling helps businesses measure and evaluate the impact of various marketing activities on sales and other key performance indicators. This analytics technique could help businesses allocate marketing budgets, measure returns on investment, forecast, and plan sales and optimize channel strategies.”
Adding on to these, let see a few more use cases and real time applications;
- Gaining insights into product performance, customer segmentation, abandoned carts, and funnel analysis, enabling businesses to improve their website design, marketing strategies, and pricing decisions.
- Tracking and measuring social media performance. Analyzing metrics on follower growth, engagement rates, post reach, and click-through rates. By analyzing these metrics, businesses can refine their social media content, identify popular trends, and optimize their social media campaigns to maximize engagement and brand awareness.
- Monitoring and optimization of digital advertising campaigns. It provides insights into ad impressions, click-through rates, conversion rates, and return on ad spend (ROAS). By analyzing these metrics, businesses can optimize ad targeting, adjust bidding strategies, and allocate budgets effectively to maximize the ROI of their advertising campaigns.
How can Digital Analytics save time and help businesses grow in a smart way?
As per Gianna, digital analytics saves time “with a clear goal and set of objectives, translated into measurable KPIs. Having a sound understanding of digital analytics in place will allow businesses to identify gaps right away and optimize marketing activities to close the gap. Data-driven budget planning has also proven to maximize investment ROI which ultimately translates to business growth.”
“Digital Analytics saves time by automating data collection and providing quick access to actionable insights. With real-time monitoring and identification of conversion bottlenecks, businesses can promptly address issues and optimize their digital strategies, leading to faster growth. Targeted marketing and personalization based on user behavior data allows businesses to focus their efforts on the most responsive audiences, saving time and resources. By making data-driven decisions and iterating strategies through A/B testing, businesses can optimize their digital operations and achieve growth in a smart and efficient manner. Overall, Digital Analytics empowers businesses to leverage data effectively, make informed decisions, and drive smart growth” says Rita.
In conclusion, digital analytics has emerged as a powerful tool in the modern business landscape, enabling organizations to harness the wealth of data available to drive growth and success. By leveraging the insights provided by digital analytics, businesses can grow exponentially. These analytics save time by enabling data-driven decision-making, streamlining reporting, and facilitating agile marketing.
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Data and Analytics: Key trends in 2023 driving new growth, efficiency and innovation in organizations
Data and analytics: Key trends in 2023 driving new growth, efficiency and innovation in organizations
As many businesses continue to find ways to optimize their operations and drive growth, data and analytics continue to be an area of investment. Organizations will continue putting in resources to ensure that they are equipped with the right infrastructure, tools and skill sets to anticipate market changes, respond and pivot accordingly, and transform uncertainties into opportunities for their businesses.
Understanding the top trends in data and analytics technology and practices therefore becomes imperative for organizations to stay ahead of the game. And whether you are a data-driven leader of your organization or team member looking to add value to what your organizations are doing, staying on top of these trends will serve you in what you do.
Artificial Intelligence (AI) and Machine Learning (ML)
As artificial intelligence (AI) and machine learning (ML) mature, so do its applications in data analytics. The use of AI and ML in data analytics help drive efficiencies in analyzing large sets of data, helping provide more accurate and insightful predictions and recommendations at a scale and speed. AI-powered algorithms can help organizations automate data analysis, uncover hidden patterns and insights, and make more informed decisions.
As more organizations across industries ramp up their search for highly skilled data analytics, AI and ML professionals, building your knowledge and capabilities in this areas can help you stay relevant and marketable. In May, She Loves Data is collaborating with Databricks to run a session on the topic of The Future of Open AI for Individuals and Professionals where we will chat with industry experts on AI revolution to discover the limitless possibilities & see how the evolution of open AI will change and impact our professional and personal lives.
Cloud-based analytics
Another trend that is pervasive in the data analytics space is cloud-based analytics, which refers to the manipulation and analysis of data that happens on the cloud instead of in an on-premises system. Analytics systems hosted in the cloud enable users to access, aggregate, analyze and utilize larger sets of data from across the organizations, subject to access and permissions control.
There are already many existing use cases for cloud-based analytics and this will continue to grow. Whether you are a marketer looking to analyze your customers’ purchase behaviours, a finance professional looking to analyze financial market data, or an ESG consultant wanting to gain insights into your client’s sustainability practices, cloud-based analytics enables additional sharing and collaboration, improved security, lower costs and tremendous scalability.
Data democratization
Data democratization refers to the process of making data more accessible to all employees within an organization. This trend is driven by the recognition that insights can come from any part of an organization, and that empowering all employees with data can lead to better decision-making.
According to The Data Warehousing Institute, in 2023, one of the most significant shift that the industry will see in 2023 is a push for more democratization in the data analytics space. Every data-driven company must realize that if they are to achieve the company-wide insights to drive operational efficiencies and growth, they need to make data and analytics tools accessible to more users.
According to Rohit Amarnath, CTO of Vertica and a Forbes Council Member, the “self-service” or “democratized” analytics model will become a “holy grail” standard that data practitioners will continue to strive for in 2023. This model, where all business units (even non-technical ones) will have access to data and intelligent insights, can be hard to set up and scale. But that should not mean organizations should not move ahead with democratizing the data and analytics. Cloud architectures, on-demand analytics platforms, continue to grow and deliver functionality to meet the demand.
What can this potentially mean for you? No matter your role and level of seniority in the organization, upskilling yourself to understand how to operate the analytics tools and make sense of the data will be key to stay relevant.
Data storytelling
Data storytelling is the practice of using data to tell a compelling story. It involves combining data with visualization and narrative to create a compelling and engaging story that helps decision-makers understand complex data sets.
As data and analytics gets democratized, the ability to make sense of data and tell a story from those insights will be critical for anyone operating in data-driven organizations. According to Harvard Business School, many companies have begun including data storytelling as a required skill in analyst job descriptions, while others have created specific roles and are hiring for data storyteller positions to supplement their existing analytics teams’ abilities. Having the skills to both analyze data and communicate its insights will make you a much sought-after talent in today’s data-driven environment.
As the data & analytics space continue to evolve and grow, so too will the kind of roles and skill sets that organizations will need to help them address their most pressing business challenges. Keeping yourself on top of the latest trends in the space and finding opportunities to upskill yourself in this area will help you stay ahead of the curve while making yourself a valuable asset for your organizations.