For years, catalogers and other “traditional” direct marketers have shared customer-level information to drive better ROI from their marketing investments. This sharing has largely been
performed through several large cooperatives. Most major postal-direct marketers are a part of these cooperatives, because the gains from joining a cooperative are so large.
similar gains available to email marketers if they share subscriber-level data with other marketers. Marketers have a wealth of data that—if shared—can drive better email programs for
Some examples of the kind of rich data that is available to marketers today:
- When are subscribers active in commercial email?
- What kind of device they are on?
- What is their current location?
- What is their recent Web site behavior?
- What kinds of offers
(discount, exclusive offers, free shipping) have they responded to in the past?
- How often has the subscriber opened, clicked, and purchased in the past?
With a large
cooperative database of this sort of data, a number of interesting customer treatments present themselves. Here are three ideas:
- Send messages when clients are active in commercial
email (and on devices where they are likely to buy now). Today, the best practice is to estimate when a client is likely to be active in an email based on historical behavior -- and to send to a
subscriber at that time. This works well, typically increasing open rates by more than 20%. What if you knew that subscribers were active in email right now, and that they were on a large
format device where they were more likely to purchase?
- Personalize the kinds of offers based on results at other marketers. I love free shipping. I am much more likely to
buy when free shipping is offered on physical goods. My wife likes “exclusive offers” for a company's best customers. These individual behaviors are consistent across many product
categories. By looking across marketers to see the kinds of offers (and calls to action, emotional concepts in the message, etc.) that drive behavior, messaging can be personalized to optimize the
chance of response.
- Build customer journeys based on “non-standard” location. I spend the majority of my time in and around beautiful Boulder, Colo. When
I’m not in Boulder, I’m most frequently traveling on business. On a business trip, I need a place to stay, meal options, a location to meet up with my teammates near our client location,
ground transportation, a place to take clients out to dinner, and many other things. Smart marketers can build great customer journeys based on the fact that they know I’m not currently at
These suggestions are only the tip of the iceberg.
What is stopping marketers from sharing data? There appear to be three major impediments to data sharing:
- Privacy is a concern. Under most global privacy regimes, subscriber-level, personally identifiable information is shareable if clients/subscribers give affirmative, informed permission to
share the data. Most marketers haven’t asked for that permission. Data collection practices and privacy policies need to be updated if data is to be shared at this level. In addition, if
activity data is shared but is tied to an anonymous token (not a plain text email address) with someone acting as a “data processor” (e.g, the cooperative), data sharing is permitted in
most countries. Many marketing teams are unfamiliar with the requirements of privacy regulation, and these “data processing” cooperatives do not yet exist at large scale.
- It’s really hard to pull this data from marketing clouds and email deployment vendors. Most “marketing clouds” haven’t invested in building solid data transfer and
API frameworks. For marketers to share data, the data transfer needs to be far easier.
- Marketers are afraid of aiding the competition. This is the most easily surmountable impediment.
After all, catalog cooperatives have been in place for years, with many competitors sharing data. Controls can be put in place to prevent sharing of data with listed competitors, and what’s
shared can be limited to data that isn’t unique to that vertical. (For example, the fact that a subscriber is active in commercial email can be pulled from any vertical.)