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One of the most common issues that seem to prevent marketers from capitalizing on the benefits of analytics is not having the budget to pay for it in the first place.

The concern isnt unreasonable: why would you spend any money at all on marketing, if you dont have a good way to measure whether its effective or not? Today Im going to show a few simple facts about returns on analytics, some success stories, and finally, a reliable method to make a case for analytics.

With the abundance of analytics tools, effective no longer means how many views, opens, clicks, likes, visits, sign-ups, plays, downloads, check-outs, leads or even sales you got.

So what if you know exactly how many people went on your facebook page or how many retweets you have this week? None of these metrics matters if you cant determine what effect the money you spend has the money you make.

As John Wannamaker famously said, Half the money I spend on advertising is wasted, I just dont know which half. Well, if John Wannamaker had had access to the kind of analytics capabilities in 1910 that we have now, he would have known exactly which half.

the age of Google, Facebook, Twitter, NetFlix, Amazon, YouTube, iPads and smartphones, when almost every customer interaction can be tracked and cheap cloud computing makes Big Data available to almost anyone with access to the Internet. With so many new paths to take in the increasingly complex customer decision journey, why would you NOT invest in analytics?

If you are not yet persuaded, or Im preaching to the choir and you just have trouble convincing your company to fund an analytics project, here are some facts, real world and suggestions that will help you make a business case.

First, since were in analytics, here are some data:

The fact is, research from some of the best minds in the business shows spending on analytics is not a sunk cost, but actually an excellent investment that more than pays for itself in net profits. Here are some of the research results.

  • Analytics-driven organizations are 2.2 times more likely to outperform industry peers than those that do not use advanced analytics. - MIT Sloan Management Review, 2011

  • Analytics pays back $10.66 for every dollar spent. Nucleus Research, 2011

  • Companies that put data at the center of marketing and sales decisions can improve their marketing ROI by 15% 20% without increasing their budgets, 2012

The evidence points towards investment in analytics, and companies have taken notice. According to The CMO Survey in 2013, marketing organizations are spending an average of 6% of their marketing budgets on analytics, but this number is expected to reach 10% in the next three years.

Four Real-World Examples

Im aware that research can sometimes sound a bit nebulous and not so applicable to your own business situation. So let me share with you four practical examples of analytics projects MaassMedia has undertaken for our clients that delivered tangible results they could take to the bank:

Case Study #1 Tracking Online Engagement Yields 13% Increase in Revenue

For one of the largest media publishing websites in the country, MaassMedia collected site behavior data using Adobe SiteCatalyst and developed a custom online engagement model allowing the company to better target visitors with ads, leading to a 13% increase in revenue.

Case Study #2 Correlating Clicks To Sales Saves $2 Million A Year

Our correlation analysis discovered a connection between clicks on product images online and future sales of those products. The correlation helped a Fortune 100 chemical company fine-tune their demand forecast model and save $2 million a year in manufacturing costs.

Case Study #3 Email Campaign Analysis Uncovers 1,429% ROI Opportunity

After analyzing three years worth of email marketing campaigns, consisting of over 450 million rows of data, for one of the worlds largest consumer electronics manufacturers, MaassMedia uncovered opportunities to generate a 1,429% ROI by nurturing higher quality leads and upselling to first-time purchasers.

Case Study #4 Channel Attribution Model Generates 10% Increase In Leads

Integrating Google Analytics Premium with DoubleClick, MaassMedia calculated the impact of each online touch point in the customer decision journey for a large telecommunications company and developed a data-driven channel attribution model that increased leads from display campaigns 10% above projections.

What made these projects successful are not necessarily the tools we had access to, the time we spent or the resources and talent we had. These projects succeeded because of good planning and good execution.

Which brings me to my next point a suggestion for how to make a business case for putting money into analytics.

How to Make A Case for Analytics: Conduct A Pilot

In my experience, one of the best ways to gain support for any marketing or business initiative requiring funds you havent budgeted for is to conduct a small pilot project or Proof of Concept (POC) test first.

Ive found it much easier to get buy-in from senior management for discrete projects that have a finite duration and low level of effort (LOE),

and that cost less than longer-term commitments. These projects would serve the important purpose of testing new ideas.

If the project fails, little is lost and youve gained valuable insight into what doesnt work. If successful, however, you will have meaningful results that hopefully will validate your theory and, at the very least, demonstrate the value in pursuing more analytics experiments.

To help ensure your pilot project achieves the results you desire, though, I strongly suggest you think hard about answering the following questions first:

1. What business problem or question will the project address?
2. What is your hypothesis?
3. How will success be determined and via which metrics?
4. What data will you need to capture and where will you get it?
5. hat actions might you take (or not take) depending on the outcome?
6. Who do you need to involve in the project for it to succeed (e.g., a business sponsor, project manager, consultant, etc.)?
7. How long will the project take from beginning to end?
8. How much will the project cost?
9. How will you communicate the results?

Once you can fully answer these questions, you are ready to draft a plan. Every good plan should include a:

  • Problem statement

  • Hypothesis/goal

  • Methodology

  • Timeline

Having a good plan in place will help ensure your analytics pilot is well executed, thus significantly increasing the likelihood of a favorable outcome. Plus, it will help you win your companys support and approval both for the pilot and for any future analytics projects by showing you did

your homework.

What to focus on for your first analytics pilot depends greatly on what kind of business you run, how your website is designed, and who your customers are.

For instance, if you are a manufacturer and do not sell directly to customers, then you may want to tailor your pilot project to finding out what marketing channels influence demand for your brand the most. If you are a publisher of content, then maybe you want to run a test on how to increase ad sales. If your site is transactional, then you should probably focus on ways to drive conversion.

No matter what, though, you should always pick something you can tie to dollars

and about which your company will actually care. Otherwise, you might as well forget about getting that budget.

In Conclusion

With all that said, analytics isnt going to solve all your problems. But now that I have armed you with a few of the latest facts about how analytics will improve your marketing ROI, some real world success stories from our clients, and my suggestion for a pilot project, I hope you are at least a little more prepared to build a business case for analytics than you were before.

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