Unit V

Digital Marketing Strategy

• A digital marketing strategy is a set of planned actions performed

online to reach specific business goals.

• In simple terms, this means performing consistent actions at the right

time via the most suitable online channels to increase revenue and
improve relationships with your audience.
Importance of Digital Marketing Strategy
• It motivates you to learn more. When you start to develop a digital
marketing plan, you need to think through every aspect of your
business. You also have to thoroughly analyze your audience,
competitors, trends, and neighboring niches to create a polished and
up-to-date digital marketing strategy. Developing a plan is an amazing
chance to get more in-depth knowledge of your business!
• It provides real data. During the analysis, and after turning your
strategy into action, you will get a lot of comprehensive data about
what works well for your brand and what doesn’t. Empowered with
that information, you’ll have a catalog of options for improving your
business.
• It structures your actions. Developing a digital marketing strategy
avoids the chaos of making blind guesses that you have to make
without having a plan. If you create a strategy, you will get a better
understanding about how to combine various marketing channels and
realize the full potential of your company.
• It helps to increase ROI. Once your actions are structured, you make
fewer actions and fewer mistakes. With a well-crafted plan, you will
be able to detect your weaknesses, predict problems, and quickly
react. You will save time, money, and efforts to increase margins as a
result.
• It helps you reconsider your relationships with the audience. A
digital marketing strategy gives you a fresh look at your
communication with prospects and customers during all of the stages
of the buyer’s journey. When you make a business plan, you need to
focus on your customers, find ways to add more value to your
relationships, and develop new ways to engage with them.
Digital Analytics

• Digital Analytics is the measurement, collection, analysis, and

reporting of data from digital channels, such as websites, mobile
apps, social media, and other digital touchpoints.

• The goal of digital analytics is to understand customer behavior and

measure the effectiveness of digital marketing initiatives, with the
goal of optimizing and improving the customer experience.
• Digital Analytics includes a wide range of data sources and metrics,
including website traffic, page views, time on site, bounce rate,
conversion rate, e-commerce transactions, and customer
demographic information.

• This data can be analyzed to gain insights into customer behavior,

such as which pages are most popular, where customers are coming
from, and what actions they are taking on the site.
The approaches and steps of Digital Analytics
• Data Collection: The first step in digital analytics is to collect data from a
variety of digital channels, including websites, mobile apps, social media,
and other digital touchpoints. This data can be collected through various
methods, such as website tracking tags, server logs, and APIs.
• Data Integration: The next step is to integrate the data from different
channels into a single data source, such as a data warehouse or a cloud-
based data platform. This allows for a comprehensive view of customer
behavior across different channels.
• Data Cleaning: The collected data may contain errors, missing values,
and inconsistencies, which need to be corrected and cleaned before
analysis. This is an important step in ensuring the accuracy and
reliability of the data.
• Data Analysis: Once the data is cleaned and integrated, it can be
analyzed to gain insights into customer behavior and the
effectiveness of digital marketing initiatives. This may involve
descriptive analytics, such as calculating metrics, like website traffic
and conversion rate, or more advanced analytics, such as predictive
modeling and segmentation analysis.
• Data Visualization: Data visualization is an important step in digital
analytics, as it helps to make sense of the data and communicate
insights to stakeholders. Data can be visualized in a variety of ways,
such as graphs, charts, and dashboards.
• Data Interpretation and Action: The final step is to interpret the data
and make data-driven decisions to improve the customer experience
and drive business value. This may involve adjusting marketing
strategies, optimizing the customer journey, or implementing new
technologies and tools to enhance the customer experience.
• Continuous Monitoring and Optimization: Digital analytics is not a
one-time event, but rather a continuous process of collecting,
analyzing, and using data to drive business value. Organizations need
to continuously monitor customer behavior and optimize their digital
marketing initiatives to stay ahead of the competition and meet
changing customer needs.
Importance of Digital Analytics
• Understanding Customer Behavior: Digital analytics provides a
comprehensive view of customer behavior across different digital
channels, enabling organizations to understand what customers are
doing and why. This information can be used to optimize the
customer experience and drive business value.
• Measuring Marketing Effectiveness: Digital analytics allows
organizations to track the impact of their digital marketing initiatives
and measure the success of campaigns and initiatives. This
information can be used to optimize marketing strategies and make
data-driven decisions to drive business growth.
• Optimizing the Customer Journey: Digital analytics can be used to
analyze the customer journey, from initial awareness to purchase and
beyond, and identify areas for improvement. This information can be
used to optimize the customer experience and drive business value.
• Improving Customer Experience: Digital analytics provides a wealth
of information about customer behavior and preferences, which can
be used to personalize the customer experience and improve overall
customer satisfaction.
• Driving Business Value: By using digital analytics to make data-driven
decisions, organizations can drive business value by increasing
revenue, reducing costs, and improving customer loyalty.
Google Analytics

• Google Analytics is a web analytics service provided by Google that

allows website owners and marketers to track and analyze various
aspects of website traffic and user behavior.

• It provides valuable insights into how users interact with a website,

helping businesses and website owners make data-driven decisions to
improve their online presence and user experience.
Key features of Google Analytics

• Website Traffic Analysis: Google Analytics can track the number of

visitors to a website, their geographical location, the devices they use,
and the web browsers they use.
• Pageviews and User Behavior: It monitors which pages users visit,

how long they stay on each page, and the sequence of pages they

navigate through. This information helps in understanding user

engagement and content performance.

• Traffic Sources: Google Analytics shows where your website traffic is

coming from, including organic search, paid search, social media,

direct visits, and referral websites. This data helps in assessing the

effectiveness of different marketing channels.

• Conversion Tracking: Businesses can set up conversion goals and

track them, such as purchases, form submissions, newsletter sign-

ups, or any other desired user actions on the website. This helps in

evaluating the success of online marketing campaigns.

• E-commerce Tracking: For online stores, Google Analytics offers e-

commerce tracking, which provides data on sales, revenue, and

product performance, allowing businesses to optimize their online

sales strategies.
• User Demographics and Interests: Google Analytics can provide

insights into the demographic characteristics and interests of your

website visitors, helping you tailor content and advertising to specific

audiences.
• Mobile App Tracking: Google Analytics can be integrated into mobile

apps to track user engagement and interactions within the app.

• Cross-Device Tracking: It helps in understanding how users switch

between different devices (e.g., mobile, tablet, desktop) during their

interactions with a website.

Real Time Data Tracking

• Real-time monitoring is the delivery of continuously updated data

about systems, processes or events. Such monitoring provides
information streaming at zero or low latency, so there is minimal
delay between data collection and analysis.

• It enables quick detection of anomalies, performance issues and

critical events.
• By tracking and analyzing data in real-time, companies can make
more informed decisions about where to allocate their resources and
how to adjust their marketing strategy on the fly. Out-of-the-box
solutions can help you optimize your marketing ROI.
Benefits of Real Time Tracking
1.Immediate Insights: Real-time data tracking provides immediate
insights into the effectiveness of marketing campaigns, allowing
marketers to make timely adjustments and optimizations.
2.Metrics Monitoring: Marketers can track various metrics such as
website traffic, click-through rates, conversion rates, bounce rates,
and social media engagement in real-time.
3.Campaign Performance: By monitoring real-time data, marketers can
quickly identify which marketing channels, campaigns, or
advertisements are performing well and which ones need
improvement.
4. Response to Trends: Real-time data tracking enables marketers to
respond quickly to emerging trends or changes in consumer
behavior, allowing them to capitalize on opportunities or mitigate
risks.
5. Personalization: With real-time data, marketers can personalize
their marketing messages and offers based on the behavior and
preferences of individual users, leading to higher engagement and
conversion rates.
Methodologies for utilizing enhanced
ecommerce in Google Analytics
• Enhanced Ecommerce in Google Analytics provides an advanced set
of features for tracking and analyzing user interactions with an
ecommerce website.
1.Implement Enhanced Ecommerce Tracking: Start by implementing
Enhanced Ecommerce tracking on your website. This involves adding
additional JavaScript tracking code to your website pages to capture
ecommerce-specific data such as product impressions, clicks, add to
cart events, purchases, and more.
2.Set Up Enhanced Ecommerce Reports: Once tracking is
implemented, set up Enhanced Ecommerce reports in your Google
Analytics account. These reports provide insights into the entire
customer journey, from product views to transactions, allowing you to
analyze each step of the purchase process.
4. Track Product Impressions: Use Enhanced Ecommerce to track
product impressions, i.e., when products are viewed by users on
category pages, search results, or product lists. This data can help
you understand which products are generating the most interest
among users.
5. Monitor Product Clicks: Track product clicks to see which products
users are clicking on the most. This data can help you optimize your
website layout and navigation to ensure that popular products are
easily accessible to users.
5. Track Add to Cart Events: Monitor add to cart events to understand
user intent and identify potential barriers to conversion. Analyze
factors such as product availability, pricing, and product
descriptions that may influence users' decisions to add items to
their carts.
6. Analyze Shopping Behavior: Utilize Enhanced Ecommerce reports
to analyze shopping behavior, such as the number of sessions that
include product views, add to cart actions, and checkout initiations.
Identify drop-off points in the purchase funnel and implement
strategies to reduce cart abandonment and improve conversion
rates.
Measuring Campaign Effectiveness
1.Set Clear Objectives: Before launching a digital marketing campaign,
define clear and measurable objectives. These objectives could
include increasing brand awareness, driving website traffic,
generating leads, or increasing sales.
2.Select Relevant Metrics: Choose metrics and key performance
indicators (KPIs) that align with your campaign objectives. Common
metrics in digital marketing include website traffic, click-through rate
(CTR), conversion rate, cost per acquisition (CPA), return on ad spend
(ROAS), social media engagement, and customer lifetime value (CLV).
3. Implement Tracking Tools: Set up tracking tools such as Google
Analytics, Facebook Pixel, or other analytics platforms to monitor
campaign performance. Ensure that tracking is implemented correctly to
capture relevant data accurately.
4. Monitor Real-Time Data: Monitor real-time data to track the
performance of your campaign as it unfolds. Pay attention to metrics
such as impressions, clicks, and conversions to identify any immediate
issues or opportunities for optimization.
5. Evaluate Reach and Engagement: Assess the reach and
engagement of your campaign by analyzing metrics such as
impressions, reach, clicks, likes, shares, comments, and mentions
on social media platforms or other advertising channels.
6. Measure Conversion Metrics: Measure conversion metrics to
evaluate the effectiveness of your campaign in driving desired
actions, such as purchases, sign-ups, downloads, or form
submissions. Track conversion rate, conversion volume, and cost per
conversion to gauge campaign efficiency.
7. Calculate ROI and ROAS: Calculate return on investment (ROI) or
return on ad spend (ROAS) to determine the profitability of your
campaign. Compare the revenue generated or the value of
conversions attributed to the campaign against the total cost of the
campaign to assess its overall effectiveness.
8. Perform A/B Testing: Conduct A/B testing or split testing to
compare the performance of different campaign elements, such as
ad creatives, headlines, targeting criteria, or landing pages. Analyze
the results to identify the most effective strategies and optimize
campaign performance.
8. Segmentation and Attribution: Segment your audience and analyze
campaign performance across different segments to identify which
audience segments are most responsive to your messaging. Utilize
attribution models to understand the contribution of each
marketing channel or touchpoint to conversions.
9. Iterate and Optimize: Continuously analyze campaign performance
data and use insights gained to iterate and optimize your digital
marketing campaigns. Test new strategies, adjust targeting
parameters, refine ad creatives, and allocate budget to the most
effective channels to improve campaign effectiveness over time.
Attribution Models

• Attribution modeling is a method used in marketing to determine

how credit for sales and conversions is assigned to different
marketing channels and touchpoints along the customer journey.
Common Attribution Models
1.Last Click Attribution: In this model, all credit for a conversion is
given to the last touchpoint that the customer interacted with before
making a purchase or completing a desired action. This model tends
to give disproportionate credit to the final interaction and may
overlook earlier touchpoints that contributed to the conversion.
2.First Click Attribution: This model attributes all credit for a
conversion to the first touchpoint that the customer interacted with
in their journey. While it provides insight into the initial point of
engagement, it may neglect the influence of subsequent touchpoints.
3. Linear Attribution: The linear attribution model distributes equal
credit to all touchpoints that the customer interacted with
throughout their journey. This model provides a more balanced
view of the customer journey but may not accurately reflect the
impact of each touchpoint on the conversion.
4. Time Decay Attribution: In this model, more credit is assigned to
touchpoints that occurred closer in time to the conversion event.
Touchpoints that occurred earlier in the customer journey receive
less credit. This model acknowledges the diminishing influence of
earlier interactions but may still overvalue the final touchpoints.
5. Position-Based Attribution: Also known as U-shaped attribution,
this model gives credit to both the first and last touchpoints, with
the remaining credit distributed evenly among the intermediate
touchpoints. It acknowledges the importance of both the initial
engagement and the final conversion event.
6. Algorithmic Attribution: Algorithmic or custom attribution models
use data-driven algorithms to assign credit based on the specific
characteristics of a business's customer journey and historical data.
These models can be highly tailored to reflect the unique dynamics
of a company's marketing ecosystem but may require more
advanced analytics capabilities.
7. Custom Attribution Models: Some businesses develop their own
custom attribution models that combine elements of various
standard models or incorporate additional factors specific to their
industry or marketing objectives.