5 Signs it's Time to Break Up with your Legacy Analytics Tool

April 19, 2019 Dan Mochel


Let’s be honest. Your analytics tool may have been state-of-the-art when you first started using it, but when was the last time you sat down and took a hard look at its features? A lot has changed in the last few years, and marketers should be demanding a more holistic view of their customer's path to purchase.

Advances in computational power, database structure and modern math are allowing marketers to reach their customers faster and drive more qualified traffic to their site than ever before. But they must be equipped with the right solutions to get the job done. So, how are you supposed to know it’s time to rethink your legacy analytics tool? Here are 5 critical signs:

1) Limited attribution capabilities

One of the most important jobs for marketers is knowing where to focus your efforts to acquire new customers and increase your return on investment (ROI). Marketers need to understand what channels are driving sales along with each and every touchpoint that resonates with buyers.

Many analytics tools are outdated and have very limited attribution capabilities (typically just first or last touch). An analytics tool that focuses on a single touchpoint does not provide marketers accurate data for where to focus their resources because it does not take the full customer journey into account. If your analytics tool does not have multi-touch attribution capabilities, you won't know for sure that marketing is maximizing results while reducing costs at every touchpoint.

2) Restrictive reporting and dashboards

Are you able to see your data the way you want, or are you shackled by frustrating limitations? Legacy tools lack fully customizable dashboards and drill-down capabilities that you need to view your data the way that makes the most sense for your business.  

No two businesses are exactly the same, yet many marketing tools try to paint their solutions with a broad stroke. This is restrictive and ultimately forces to marketers to adapt to their solutions, rather than the other way around.  

If you find yourself digging through countless reports, exporting data to excel, or sacrificing visibility into your business because your analytics solution simply won't report on something, it's probably time for an upgrade.  

3) Limited view of the customer journey

Most cross channel measurement and attribution tools only look at traffic when it is one step away from your website. Because of this, most marketers only have visibility into about 20% of the entire digital actual ecosystem. However, consumers are often researching, evaluating, and considering your products or services long before they ever reach your site.

To truly gain a holistic view of your customer's path to purchase, you need to understand their journey across the entire internet, not just when they are one degree of separation from your website. A cross channel measurement solutions should help you understand what your competitors are doing to effectively drive traffic. Armed with that knowledge, marketers can step in front of their competitors marketing tactics and redirect highly qualified traffic to their own website.

4) Inability to keep up with the rapid pace of change

Marketing is evolving quickly, yet legacy analytics tools have remained largely the same. A true solution should keep up with the rapidly changing digital ecosystem. Features like multi-touch attribution, algorithmic attribution, complete ecosystem visibility, identity stitching and media agnostic behaviors should be the new normal if marketers expect to keep up with changing consumer preferences, splintering channels, and competitor expansion.

5) Lack of forecasting and ROI

One of the largest hurdles in marketing is that it's difficult to quantify the entire value of a campaign. Measurement solutions have not kept up with the growth in channels or devices, and that makes it difficult to report on the results, let alone predict the value of a campaign in advance. 

With machine learning and artificial intelligence, it is possible now to forecast campaign returns at the channel, campaign, or even source level. This makes it easier for marketers to get C-Level buy-in for new initiatives and builds trust between marketing and other business units.

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