The Need of Data Science in Digital Marketing

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The Need of Data Science in Digital Marketing

• Digital Trainee

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Data ScienceIntroduction

• Data science is an field responsible for
  managing, manipulating, extracting, and
  interpreting information from massive amounts of
  data.
• 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.

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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
  needs.
• 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.

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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

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Campaign Strategizing

• One of the main purposes of implementing data
  science is planning a campaign that performs
  well.
• 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.

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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.

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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.

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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
  techniques.
• 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.

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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
  customers.
• PPC (Pay Per Click) Optimization
• Optimization of Retargeting Marketing Data
  Science
• Prediction of churn
• Optimization of email campaigns
• Personalized messaging
• Message timing optimization
• Pattern recognition of clients and prospects

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