I got a travel related email this morning, informing me that “New York missed me.”
First of all, I didn’t realize that New York knew me well enough to notice, but that’s a story for another time. More important, and why I am relaying the story, is that I booked with this same company twenty four hours earlier to spend time in The Big Apple over MLK weekend. So while I’m being told that, “New York misses me,” I’m thinking, “New York may need a better social secretary.”
Here’s the linear flow:
– Tuesday evening, I check rates on provider websites, evaluating whether or not to pay or use rewards I have on hand. Note that this was not on third party sites, but specific, corporate sites where I was logged in and recognized as an existing customer.
– Wednesday morning, I book all my travel, and start the mental countdown to a weekend in Manhattan with my kiddo.
– Thursday morning, the request to visit from the Big Apple arrives, which leaves me shaking my head, and quickly checking to make sure that my reservation did, in fact, make it through the system.
In theory, no harm, no foul, but I can’t say that the few minutes of scrambling to make sure that things didn’t get lost left me with a warm fuzzy. To the provider, it’s no harm, no foul. They can chalk it up as booked revenue and move on, right?
Or should they?
See, not only did I book, I’m supposed to be one of their top tier, most lucrative customers. They tell me that in other communications, in the greetings they send me at the end of the year, with the rewards they leave me when I hit certain milestones. So by trying to push me over the line on that one trip, they are actually undermining the work they’ve done at a macro level to make me feel loved and valued. It’s the difference in an event versus a relationship, prom vs. marriage, and when it comes to the long haul, it can make or break the dynamic of the entire consumer experience.
Now, before you think that I’m unfairly picking on this one provider, I see it in multiple places. Recommendation engines telling me to read XYZ when I checked it out via my library through the incenting company’s server months before. A reminder that something is in my cart, when I went into the store a few days before and made the purchase in person. It’s an equal opportunity cycle folks, one in which I’m seeing a number of slip ups, but not much action to address.
Okay, Heather, if you’re so smart, what would you do to prevent these gaffes from happening? You aren’t really recommending that we can course correct for everything, are you?
Nope, I most definitely am not. There’s nothing you can do if I buy something thirty minutes before you drop a contact. People are realistic enough to understand that things can’t always be real time. On the flip side, if you are advocating for an omni-channel, seamless experience, and miss the boat by more than twenty-four hours, that isn’t a pardonable excuse, and it exposes holes in your data capture and recognition processes.
Let’s go back to my travel experience. The process in which I was targeted is the equivalent of an abandoned cart – I executed a search specific to New York, and within 24 hours hadn’t booked, so an email was spooled off and sent reminding me of the open transaction. This is often an automated process, wherein if I have not acted within X period of time, a contact goes out, reminding me to act. This could be email, a social media message, a banner, even a phone call, but it needs to happen in near real time from the point of action, so that you don’t have a gap (like I did) between when the contact (driven by data) is cut and when the touch is made (as executed by marketing).
Solving the problem in 4 easy steps:
- Create a full list of the conversations you’ll be driving (e.g. my New York misses you contact)
- Evaluate what data is available to drive the contact, as well as how frequently it’s updated
- Determine how important a semi-real time contact is, and then reconcile that with frequency of data update, as well as how many different channels the individual could act in.
- Using inputs 1-3, determine a minimum and maximum contact window, and the appropriate business rules to address an action or inaction.
It’s important that, when thinking about point 4, multiple examples (or use cases) are played out. You may very well find that there’s a latency issue in the data, which can be solved with more frequent updates or smarter consolidation of data. On the flipside, you may also realize that you’re undermining yourself if a message should be real time, but has a significant lag, like I experienced. The parental wisdom as it relates to the latter is best described as ‘just because you can, doesn’t mean you should…’
Finally, just because you solve for the problem once, doesn’t mean that it’s solved forever. Changes in feeds, timing of updates, and constantly evolving expectations mean that you have to stay on top of your conversations. Just like my New York example, there’s an impact to the timing of a communication and the type of customer you are talking too. To beat the metaphor to death, if I’m that special, you don’t want to mess up on asking me to prom and risk the long term health of our relationship, especially when it’s over things as simple as data and timing.