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The Need of Data Science in Digital Marketing


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Title: The Need of Data Science in Digital Marketing

The Need of Data Science in Digital Marketing
  • Digital Trainee

Data ScienceIntroduction
  • Data science is an field responsible for
    managing, manipulating, extracting, and
    interpreting information from massive amounts of
  • Data science (DS) is a multidisciplinary area of
    research aimed at addressing big data challenges.
  • In these modern times, the very existence of
    Digital Marketing strategies would be doubtful
    sans the presence of Data Science.

Role of Data Science in Digital Marketing
  • Data Science helps in removing guesswork in SEO.
  • Instead of assuming the results of your work,
    data science will help in finding out the results
    and success of work.
  • Data science will help in get entire information
    of customers like their choices and needs from
    which one can run campaign according to customer
  • Marketers may use Data Science to gain access to
    utility groups of data collected across a variety
    of platforms, including organic (SEO/website
    analytics), social media, and email marketing.

Benefits of Data Science for Digital Marketing
  • The following is a list of some of the advantages
    of using data science in digital marketing.
  • Campaign Strategizing
  • Optimization of channel and budget
  • Increase in the speed of planning
  • Customer aligned data that is real time

Campaign Strategizing
  • One of the main purposes of implementing data
    science is planning a campaign that performs
  • Data science facilitates marketers to segment
    customers according to their buying habits,
    demographics, and geo locations.
  • This also make other tasks like planning, SMO,
    budget allocation simple, allowing you to build a
    strategy that resonates with the needs of your
    consumers and produces better results.
  • Data science will also help you identify your
    most valuable customers and provide them with
    better benefits than the rest of your audience.

Optimization of channel and budget
  • Data Science helps the business that operates
    through channels like social media, sites, etc.
    by optimize those channels for getting the best
    return on investment (ROI).
  • Data science allows you to see and assess your
    campaign's success rate, as well as identify
    problems from past campaigns.
  • Via data science, you can get the percentage of
    people who are engaged and patterns in their
    actions on each of your platforms.
  • Though the results can differ across channels and
    platforms, the goal is to determine and test
    which performs better at any given time.
  • Traffic data analysis helps you in determining
    and allocating budget for channel differently.

Increase in the speed of planning
  • Marketers are able to do faster and easy planning
    of their campaigns with the aid of Data Science.
  • Businesses already has data on their website,
    social media channels and on the existing
    campaigns. Data Science helps in the gathering
    and analysis of data in a more precise and
    efficient manner. 
  • This allows businesses to design and execute
    campaigns more effectively, resulting in a higher
    return on investment.

Customer aligned data that is real time
  • With the help of Data Science current and future
    digital marketing campaigns can be designed as
    per real-time data by focusing on current market
    trends and consumer trends.
  • Data regarding market trends, execution time
    efficiency, customer behavior, and buying trends
    is retrieved using existing data science
  • This is especially critical when it comes to
    identifying new opportunities, forecasting
    patterns, and outsmarting competitors.
  • With cleverly designed marketing content, loyal
    customers can be efficiently targeted at the
    right moment.

Data Science in Marketing
  • Predicting the content would be well-received
  • Predict which social media platforms the
    prospects are most likely to use
  • Estimate which deals would appeal to which
  • PPC (Pay Per Click) Optimization
  • Optimization of Retargeting Marketing Data
  • Prediction of churn
  • Optimization of email campaigns
  • Personalized messaging
  • Message timing optimization
  • Pattern recognition of clients and prospects

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