Savvy email marketers now have the ability to rapidly send precisely targeted, relevant campaigns, driven by a wealth of customer data collected from different sources.
Organizations are investing in making even more customer data available to marketers, based on the premise that more data will improve marketing results.
Faced with so many possible improvements, how do we identify the best opportunities to pursue – those we can accomplish quickly and count on to actually improve our marketing performance? We want to uncover the most impactful avenues to pursue first.
Start by making a list of potential projects and evaluate each opportunity against the following criteria:
• Which are most likely to improve KPIs?
• Which are most feasible given our timeline and budget?
• Which is easiest to accomplish and will produce measureable results?
Let us imagine a fictional company: Cappos.com, a casual clothing retailer for men, women and children. The marketers at Cappos.com now have access to on-site analytics data by user, cart status, shopping history and certain demographic information. Currently, they are only using cart status to drive a rudimentary abandoned cart program, which simply sends customers a reminder that they have abandoned their cart. It does not identify which products have been abandoned.
Let’s examine Cappos.com’s options using the three criteria above, to identify which program changes they should make first, given their new abilities.
1. Which Are Most Likely to Improve KPIs?
It may seem odd to ask this question before understanding what is feasible, but you can often get much better results by having an end goal in mind before gauging feasibility. You may be able to find or reallocate resources once there is a compelling vision to work toward.
Cappos.com now has easy access to the following new data:
• On-site usage data by user
• Cart status and shopping history
• Some demographic data
Here are just a few of the potential improvements they can pursue:
Cappos.com could use the new cart status and shopping history data to improve their abandoned cart program with more relevant content, including the actual products abandoned and relevant promotions based on past purchase history.
They could combine on-site usage and shopping history data to identify and leverage a customer’s affinity for certain products and categories on their site, then use that insight to personalize future promotional and service messages.
They could take demographic data and make assumptions about which products to highlight, based on informed assumptions about the preferences of particular demographic groups.
After Cappos.com compiles this list of possibilities, they evaluate which option will provide the greatest improvement to their KPIs. Of the three options above, the marketers decide that Option 3 is a gamble, while Options 1 and 2 show strong potential as campaign improvements.
2. Which is Most Feasible Given Our Timeline and Budget?
Next, Cappos.com does a deep-dive assessment of Options 1 and 2, to determine the requirements to make each option a reality.
Option 1 Requirements
In order to create an enhanced abandoned cart campaign, the marketing team would need to create new templates that dynamically populate messages listing the products in the user’s cart, as well as the price the user originally saw. They would also need to build some sort of rule about that user’s adoption rate of certain promotions, to decide whether to offer free shipping or a percentage discount.
Finally, the marketers would need to have a near real-time feed of user data, so they could avoid sending the abandoned cart program to users who had since purchased.
Option 2 Requirements
In order to personalize promotions based on on-site behavior, the marketing team would have to build several rules to associate behavior metrics with affinity (ie.: time spent in different categories, products in a single category purchased as percentage of total purchases, etc.). These rules could be basic or more complex, but something would need to translate what the customer did into a specific message that the customer would receive. Cappos.com would also need to remake some of their templates, adding the ability to insert dynamic content based on customer record. They would need to plan for multiple versions moving forward, making sure they curate the content for all possible variations.
In this step, the marketers at Cappos.com are beginning to create a project plan around implementing new data insight into their programs, while simultaneously evaluating whether or not the required investment will be worth the potential gains. After considering the requirements for the two options above, Cappos.com decides that both campaigns will require some investment, but both are feasible given their current access to data and ability to create and manage new content.
3. Which is Easiest to Accomplish and Will Produce Measureable Results?
Cappos.com must now identify which option – Option 1 or Option 2 – is easiest to accomplish and measure improvements. Note that this is effective only after they have thought through the aspects of possibility, benefits and which capabilities and resources are required. Beginning your option evaluation on this last step is a mistake; if the marketers at Cappos.com had started here, they would likely have rejected several viable options as too difficult, unfeasible or unlikely to deliver results.
Reviewing the remaining options, Cappos.com decides that Option 2 will be easier to accomplish since it does not require the real-time link that Option 1 requires, to avoid emailing people who have completed their cart. They also decided that Option 2 is more likely to show results quickly, since the reach of all promotions and service messages that will change is greater than the reach of the abandoned cart campaign. They decide to pursue Option 2.
Get Over Analysis Paralysis with Methodical Opportunity Evaluation
This theoretical situation faced by the fictional company Cappos.com is similar to the situation faced by many email marketers today. The abundance of potential customer data insights that marketers can pursue to improve their campaign performance is overwhelming – so much is possible, and it can be difficult to decide which options to invest in first.
By analyzing opportunities in a structure similar to the example shown above, however, marketers can overcome ‘analysis paralysis’ and focus on making the promised benefits of big data become a reality.
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