1. How do I organize my account?
2. What kind of data can I access?
3. Why should I set up goals?
4. What is a segment?
5. How can I find out more about my (not provided) keywords?

This is a PROVEN WORKING SOLUTION with filter expressions updated regularly! There are a lot of partial solutions and misinformation out there about clearing out so-called referral spam (and organic search and event spam too), so here’s the Definitive Guide to removing all of that junk! This article has been constantly updated since January 2015 and has shown over 330,000 people how to get rid of spam in Google Analytics reporting.

The process in summary, proven effective for over 24 months:

• Have a new website? Use a ‘-2’ or higher property
• Implement a Valid Hostname Filter to eliminate ghost visits
• Implement Spam Crawler Filters to eliminate the targeted spam visits
• Create a Custom Segment with these filters to use for reporting
• Turn on Google’s bot & spider filter option

All the information you need is provided below in this step-by-step guide, but you will need to update the filters as they change.

Marketers will be more accountable than ever. The mindset shift means moving beyond the KPIs we have been used to and connecting the dots across from strategy to execution to performance. This means starting with the business goals and tracing the path to determine the key variables that lead to those goals. It also means injecting more information to better inform communication strategies:

• Qualified leads: Use behavioral and social data to verify prospect leads and identify false positives.
• Enrich customer profiles: leverage behavioral and profiling information to enhance knowledge about your customers. 
• Machine learning will also enable scoring systems to develop best-fit models that define audience segments, product matches, affinities and customer value.
• Developing an end-to-end accountable framework: Acquisition to retention will require continuous optimizations based on updated market and customer data to improve performance.

*Create the role of chief analytics officer -- Employed by organizations in diverse industries, including Duke University Heath Center, Macy’s, GoDaddy, EY, and even the City of New York, this role is responsible for mapping analytics needs and use cases throughout an organization. With a direct line to the C-suite, chief analytics officers match business needs and problems with analytics technology for answers.

*Form a cross-functional analytics team -- Bringing HR, marketing and other functional personnel together with IT can be one of the most beneficial ways to bridge the gap between IT and end users. Enabling these users to become citizen data scientists and use predictive analytics for their own unique needs creates meaningful results for everyone involved.

Many executives are raising questions about the reliability of the processes used to gather information. This is in addition to growing concerns about how best to maintain the privacy of their customers while doing so.

According to a July 2016 report by KPMG, which looked at how marketers could “build more trust” into their analytics and data-gathering processes, one problem with current analytics methods is executives aren’t always confident in the results. When asked about the most trusted stage of their analytics-gathering process, 38% said it was the very first step, which was data sourcing. For every stage of the process after that, marketers said they had significant doubts. Only 21% of executives said they trusted their analysis or data modeling, while just 10% said they trusted how they were currently measuring the effectiveness of their analytics efforts.

Adoption of unified marketing impact analytics (UMIA) is growing as marketers prioritize creating a data-driven approach to marketing investment decisions and realize the importance of maintaining a 360-degree view of customer interactions.
 
UMIA requires buy-in and coordination from all corners of the organization. This report specifically maps out how the internal marketing, customer analytics, technology, and finance organizations, along with third-party partners should divvy up responsibility in tackling marketing measurement.

Historical analytics
Today, Google Analytics is the most common of these tools. It’s great at telling you what happened yesterday, last week, last month. How did our marketing efforts perform? When used correctly, it allows you to adjust your marketing plan, as historical evidence demonstrates you’re not going to reach your goal in time. 

Real-time analytics
Savvy marketers are now starting to embrace real-time analytics. No longer do they have to wait until the next day or week to see the impact their marketing efforts are having. When used correctly, real-time analytics not only allows for quicker adjustments to marketing plans, it can also save thousands of dollars by killing efforts that fail right from the start or by giving a boost to those that are working. This ensures a higher ROI than if you waited a few days to review the data.

Predictive analytics
The best way to explain predictive analytics is that it’s the next generation of analytics, leveraging the power of historical and real-time analytics. Today, analysts can leverage the power of real-time analytics, making near-instant adjustments to their forecasts and allowing a nimble marketing team to make adaptations to their campaigns on the fly, avoiding potential disasters.

Perhaps the key metric of relevance is how well you actually solve the problems that your audience are experiencing. If your content answers a query in an effective manner, then you are delivering precisely the sort of user experience that search engines want to promote.

How you tangibly measure this will sometimes depend on the query that you are serving. A very simple query can be served extremely quickly with a single page, whereas more in depth queries will require much more detailed, long-form content.

Using another of our internal tools, known as Roadmap, we can start to identify correlations between both known and potential ranking factors, with high search ranking positions. The more strongly that high-ranking websites score for particular factors, the stronger the correlation.

The graph above demonstrates how particular factors, in this case those that are indicative of a strong user experience, with higher search engine rankings, correlate with higher search ranking positions.

Marketing Strategy - B2B marketers say the most important goal of their data management strategy is to improve ROI measurability, according to recent research from Openprise and Ascend2.

Marketers unanimously agree on the need for analytics, but not all are as yet committed to investing in it. All the respondents we spoke with agreed that marketing analytics was important for
their marketing success. 84% of them rated it as very important; the remaining 16% rated it as somewhat important.

• Head on over to the Admin section of Google Analytics and scroll down to Calculated Metrics. Select ‘Percent’ as Formatting Type.
• Start typing the name of the goal in the Formula field and it should appear in a dropdown. Select it. Space. ‘/’. Start typing users and select it as well.
• Name your metric — ‘goal name’ by users CVR and hit Create.

1. Start with a plan

2. Be sure you’re capturing all the data you need

3.Create the right reports for the right stakeholders

Bonus tip: check out the recently launched Google Data Studio to make beautiful dashboards from all our data sources for free.

4. Always include an executive summary with anticipated reports

5. Start to learn and become proficient in marketing forecasting

If you are a data analyst that wants to access your data with SQL check Mode Analytics and Periscope. for open source kind check Re:dash

If you need quick, useful and beautiful dashboards check Geckoboard and Geckoboard. Want to take it a bit further? Check Leftronic and Klipfolio.

Not an SQL-savvy user? Check Chartio

Are you a data analyst that wants to easily explore your data sets? Check Looker

Want to have the best visualizations? Check Tableau.