Ask a marketer if they benchmark and the answer will be yes – against competitors, peers, and channel-specific KPIs. Without an accurate benchmark to measure against, it’s hard to know how well you’re really doing–and these benchmark levels can move over time as your business and consumer behavior changes. Retail and brand marketers will know benchmarks like conversion rate and units per order by traffic source, percentage of catalog sales by month, and shopping cart abandonment rate. B2C and B2B marketers will know key performance benchmarks for their website, paid media, and email marketing.
Ask a marketer if they benchmark within their own data and the answer might be yes, for select campaigns, website metrics, and product sales. Ask a marketer if they benchmark all of their data every single day, and the answer will be no (and they’ll likely add “of course not, that’s impossible!”).
But it is possible. Outlier is benchmarking data today—each and every day—for leading brands. And also detecting when benchmarks should be adjusted to a “new normal” and what those new levels should be. Specifically, Outlier is:
- Utilizing AI-powered automated business analysis to query in some cases as many as 200K different time series and 1.2M time series data points.
- Establishing benchmarks for every metric in related segments across those time series using sophisticated trend detection modeling algorithms.
- Spotting hundreds of potentially important anomalies against those benchmarks.
- Sending a handful of the most important insights to marketers each morning, including benchmark stories.
Wait…what? Benchmark stories explained.
The above was a bit of a dense read. Let’s look at the following benchmark story and then come back to how amazing it is that Outlier can do benchmarking on first-party data at this scale…
- The icon top left indicates that this is a benchmark story.
- This happens to be a weekly story (Outlier creates daily, weekly, and monthly stories).
- The headline tells us that New Users (a Google Analytics metric) from Source: direct (Source is another Google Analytics metric and refers to a specific acquisition channel like paid search, organic search, email, social, but in this case it’s direct, or unattributed traffic to the website).
- The blue line chart shows actual new users each week from direct website traffic.
- The orange line chart shows what new users should be from direct traffic to the website based on the majority of actual values across various other Source channels (again, paid search, organic search).
So something happened starting February 28th that is driving more new users from direct traffic to the website than should be the case. In fact, new users are up a whopping 27% from direct traffic but down 26% on average across 39 other segments. And four other metrics are also moving along with new users: unique users, exits, sessions, and unique page views.
It also suggests areas for further investigation, which is something we discuss more during one of our personalized demos. I encourage you to schedule a demo to learn more!
The marketing use cases are endless…
Imagine having a product able to create benchmarks for your web traffic, email, social activity, paid media, online and in-store traffic, sales data, search activity and more. And then sending you stories like the above example when actual results start deviating above or below those benchmarks. Your daily Outlier feed will also include insights in the form of other hugely valuable story types like spike/drop, launch performance, milestone, new normal, rank, relationship, plus various data quality stories.
Forrester calls companies able to leverage products like Outlier “insights-driven businesses.” I’d encourage you to download a free copy of the Forrester Research report Enable An Insights-Driven Business, to learn more about how 7% of your competitors have already made this leap and are likely innovating faster, driving superior top line growth, and building resilience in the face of what appears to be a new normal of constant change and disruption.
And the frequency and scale of this analysis are mind-boggling.
Call your analytics team and ask with a straight face if they can please benchmark all of your first-party data across every time series segment, metric and data point, and then give you updates whenever a really interesting deviation from those benchmarks happens. After they say “No!” and explain why that’s not possible, please contact us or schedule a demo.
And don’t hold it against them. No analytics team armed with traditional BI tools can perform analysis on this scale. Way back in 1997, Deep Blue beat Garry Kasparov in the second of two six-game chess matches, and AI has been winning ever since. But in this case, Outlier actually increases the value of your existing analytics talent and tools and doesn’t replace them. Outlier points your existing analytics expertise at the actionable and potentially important insights that it surfaces each and every day. Outlier will help your analytics team to know exactly how they should spend their day, saving them time and money, by allowing them to focus on what is truly impacting your business at that moment.