Thank you to all who joined us for our webinar, Google Analytics 101.
In our 20-minute webinar, we covered actionable tips on using Google Analytics to effectively analyze your business data.
Watch the webinar recording to learn must-know terminology, best practices for maximizing your data, and easy-to-use reports for harnessing the insights you need to better to measure your marketing and website success.
Today’s data-driven marketers struggle to track and measure campaigns spanning a variety of disparate channels, technologies, and audiences. Reporting is time consuming and overwhelming, especially when you manually pull reports from each tool and cobble the insights together. Luckily, a business intelligence (BI) tool, like Domo, is a lifesaver for the time constrained, data-driven marketer.
BI tools turn huge swaths of data into simple visualizations (called “cards” in Domo) to cut through the clutter and reveal the big picture. By letting us connect disparate data sources into a single system, we can layer and analyze complex data instantaneously, without the typical headaches associated with manually pulling reports (and pulling our hair out).
Today, we’ll highlight a few Domo cards demonstrating how combining data sources in a BI tool offers deeper, actionable insights to improve your marketing strategy and business.
Ever feel like Stretch Armstrong – pulled in too many directions?
If you’re like most sales, e-commerce, and marketing teams, you face an overwhelming daily task list that leaves too little time for the fun stuff – analyzing results, optimizing performance, and strategizing your next big sale or campaign.
We’re lucky to have more opportunities than ever to engage our omni channel customers. Accenture reported that multi-channel customers (visiting a combination of our website, social networks, sales reps, and in-store) are 15% more profitable than digital-only customers and 25% more profitable than human-only experiences. The opportunity is huge, but means we’re creating more campaigns, analyzing more data, and ultimately, juggling more balls.
B2B vendors are already in the holiday marketing swing to help their retailers fulfill inventory, while B2C brands are brainstorming and executing holiday campaign strategy for their stores, websites, emails, and more.
Everyone wants a piece of that huge holiday pie. Last year, holiday sales during November and December increased 5.5% over 2016 to $691.9 billion.
A smart digital strategy is step one to getting a big, fat piece of that seasonal spending. Of course, the best way to map out a winning digital strategy is to first look back at what worked last year.
To get started, we’ve outlined 3 Google Analytics metrics to benchmark from last season to help you develop this year’s marketing plan.
Conversions + most popular shopping days
First, identify the days your website saw the highest conversions last year.
To benchmark high-level conversion numbers from last season in Google Analytics, navigate to Conversions > Ecommerce > Overview.
The Overview graph at the top of the page displays the E-commerce Conversion Rate by default, but can be modified by clicking the dropdown. You can click “Select a Metric to add additional metrics, like Average Order Value, Quantity, Revenue, Transactions, and Unique Purchases. We selected Revenue and E-commerce Conversion Rate.
In June, Google announced changes to their Google Ad suite branding, effective July 2018.
To streamline the user experience across both small- and enterprise-level businesses, and simplify their brands, Google consolidated their current offerings into three new ad brands. The new ad suite includes: Google Marketing Platform, Google Ad Manager, and Google Ads.
Last month, we announced that Google AdWords is becoming Google Ads. Starting today, you will begin to see the new Google Ads brand reflected across our product, Help Center, and other channels. This will take several months to roll out fully. Learn more: https://t.co/E2rqPY3AJ2pic.twitter.com/V6KB0xoRJg
Thanks to everyone who joined us for our May webinar: Predictive Analytics 101. We introduced predictive analytics and demonstrated simple to sophisticated predictive analytics use cases, like how to identify at risk customers and re-engage them to reduce customer churn. Below, you’ll find the webinar recording, Mud Pie case study, and slides we promised you.
Marketers use email and website personalization to deliver a hyper-relevant online experience to every customer, but succeeding with online personalization isn’t easy.
According to Evergage, 88% of marketers say their customers expect a personalized experience, while 55% admit the marketing industry isn’t personalizing to those standards. What’s more, 46% of marketers would give their own company’s personalization efforts a “C” grade, or less.
Developing user personas is key to executing a successful personalization strategy. Personas, fictional representations of key audience segments, help marketers understand the needs and interests of their audience segments, so they can make their customer journey more personal and relevant.
To get started, we collect and analyze available data (both qualitative and quantitative) to understand what makes different audience segments tick, so we can group them within logical and actionable personas. Today, we’ll walk through how to use Google Analytics Demographics and Interests data (a free tool) to capture additional quantitative data to develop detailed personas.
(Already have your data? Get detailed steps on creating user personas and our handy persona worksheet here.)
Google is beta testing a new landing page testing and optimization tool that integrates with Google Analytics and Google Tag Manager called: Google Optimize.
Doesn’t This Already Exist?
Sort of. Google has been trying to get into the optimization game for a while now. It started with Google Website Optimizer which was discontinued in 2012 for Content Experiments in Google Analytics. This brought A/B testing into the Google Analytics tool. Google Optimize is their latest iteration. Google Optimize 360 is also in beta, but the main difference between Optimize and Optimize 360 is price. Google Optimize (sans 360) is free and thus a little more limited than the 360 enterprise version.
The Google Analytics 360 suite is the premium, paid-for suite of Google products. There are free versions of these but they have some limits to their capabilities.