Wrap-up

1. Wrap-up

Congratulations on reaching the end of this course, and thanks for taking it! Hopefully, we have a better understanding about what marketing analytics is.

2. Recap

First, we learned about the basics of being a Marketing Analyst. We have an understanding of which marketing levers to analyze, as well as which business questions we will encounter. In Chapter 2, we learned about the various complexities that go hand-in-hand with marketing analytics. Understanding privacy laws, knowing where to access marketing data, and anticipating Indirect channel impact are just some of the challenges we can now face head-on. In Chapter 3 we covered some examples of common deep-dive marketing analyses. We can understand text or sentiment analysis, audience segmentation, and even run predictive models for an integrated campaign! Finally, we spent time learning about the goal for all of marketing analytics: measuring marketing ROI. By selecting the right KPIs, building forecasts, and choosing an attribution model, we can combine all of these parts into a full LTV to CAC model.

3. Follow up

For further deep dive into the world of marketing analytics, here are a few DataCamp resources to consider.

4. Congratulations!

Once again, thanks for taking this course. Best of luck in the journey to becoming a Marketing Analyst!

This exercise is part of the course

Marketing Analytics for Business

BeginnerSkill Level

4.8+

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What does a marketing analyst do? Why is this role in high demand? In this chapter, you’ll learn about roles and business questions that a marketing analyst encounters. From revenue impact to campaign insights—you'll find that marketers will never run out of problems to analyze.

Exercise 1: Marketing lever fundamentals Exercise 2: Campaign attributes Exercise 3: Channels and tactics Exercise 4: Lever hierarchy Exercise 5: Marketing roles Exercise 6: Internal partners Exercise 7: External partners Exercise 8: Marketing business questions Exercise 9: Marketing roles and business questions Exercise 10: Marketing roles and KPIs

Marketing analytics is not for the faint of heart! Between numerous data sources and ever-increasing privacy legislation, marketing analysts must consider multiple factors in reporting. Add in measuring the indirect impact of marketing, and you’ll see why marketing analysts get extremely comfortable with imperfect data.

Exercise 1: Marketing data sources Exercise 2: Internal vs. advertiser data Exercise 3: Channel granularity Exercise 4: Audience targeting insights Exercise 5: Privacy laws Exercise 6: GDPR assessment Exercise 7: Cookie types Exercise 8: Indirect impact of marketing Exercise 9: Direct vs. Indirect channels Exercise 10: Blurred lines of channel impact

Now that you know more about the marketing analytics landscape, let's talk about how you can use it to assess campaign performance. To do this, you’ll dive into text and sentiment analysis, audience segmentation, and predictive analytics. Marketers and executives rely on analytics to send the right message to the right people at the right time.

Exercise 1: Text analysis Exercise 2: Branded and non-branded keywords Exercise 3: Paid search analysis Exercise 4: Sentiment analysis Exercise 5: Social media comments Exercise 6: NLP or manual sentiment analysis Exercise 7: Audience segmentation Exercise 8: Segmentation data options Exercise 9: Cluster analysis attributes Exercise 10: Integrated campaigns Exercise 11: Campaign stages Exercise 12: Integrated campaign planning

The big question every marketer asks is "did my marketing efforts make any money?" To answer that question you'll have to consider: seasonal patterns, business model, campaign goals, and ROI. Most importantly, you’ll be responsible for setting and measuring KPIs to evaluate marketing effectiveness.

Exercise 1: KPIs and metrics Exercise 2: Marketing funnel Exercise 3: KPI vs. supporting metric Exercise 4: Marketing forecasting Exercise 5: Forecast requirements Exercise 6: Forecasting process Exercise 7: Attribution modeling Exercise 8: LTA vs. MTA Exercise 9: Identify attribution model Exercise 10: Revenue and cost modeling Exercise 11: Spend and revenue considerations Exercise 12: CAC and LTV calculations Exercise 13: Wrap-up

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