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An “FU Meter” measures aggregate negative responses to a text messaging campaign. While standard opt-out monitoring captures responses to explicit commands like STOP, END, or UNSUBSCRIBE, the FU Meter also tracks less formal replies such as “who is this?”, “please take me off your list”, or commonly, variations of “f%$# you” (hence the name). This tool is essential for any sender. If their messaging platform does not include it—and ideally, all platforms should—it’s relatively simple to create a jerry rigged solution using a spreadsheet, a Jupyter notebook, or even ChatGPT.
The Purpose
The meter watches for poorly designed campaigns that are missing the mark, i.e., a text messaging campaign that elicits a high level of negative responses from the audience. For reasons often related to the recency of the list or the relevance of the message, the incoming text message feels like an invasion and gets a negative, at times nasty, response from the recipient. This is understandable. Intolerance for an unwanted text message (see sidebar) is superseded only by the intolerance for an unwanted phone call.
Sidebar: Defining Unwanted Text Messages
The problem with colloquial usage is that it doesn’t allow for precise conversation. Terms like spam, phishing, unwanted text messages, political text messaging, marketing, promotions are used so interchangeably that message classification becomes a porridge of mixed definitions and unclear distinctions. Last year, I took a stab at clarifying definitions using examples (the only way I know):
Wanted: Your dentist, whom you recognize, sends you a reminder about your upcoming appointment.
Unwanted: The same dentist sends you coupons offering 50% off your next cleaning without any prior notification. Remember, unwanted does not mean useless. You might still appreciate the coupon but choose to opt out!
Spam: A dentist you’ve never heard of sends you discount offers on teeth whitening.
Phishing: You receive a suspicious link from an unknown number claiming you can claim a free teeth whitening package.
The Metric
What’s a good percentage? Is it 0.5% of total traffic? or is it less than 2%? The correct answer is that it depends on the use case and the industry. For your standard run-of-the-mill marketing use case, your standard opt-outs should be 2% or less, and your negative response rate should be less than 3-4%. In some industries, like political messaging, a high opt-out rate might reflect more on the candidate or the cause than the campaign itself, hence the caveat. Suffice to say, your FU metric will always be higher than your actual opt-out percentage.
How to deal with a high number?
Most often, a high percentage boils down to three issues: the recipient either doesn’t know who you are or is receiving a message they don’t recall signing up for, or didn’t sign up for at all (also known as campaign drift). You could conduct a detailed Recency, Frequency, and Monetary Value (RFM) analysis, or simply maintain basic list hygiene.
For example, before you upload your Excel spreadsheet to your messaging platform, ask a few critical questions: “How long ago did you last engage with your customer?” “Will they recall your relationship fondly when they receive your message?” “Will they even recognize who you are?” If the last time you reached out was during last year’s Christmas season, will they remember you when you send this year’s Labor Day greeting?
Employing double opt-ins is always a wise practice, especially when it has been a significant time since your last communication. If the time gap isn’t an issue, sending reminders explaining why they signed up and the benefits of staying connected can be very effective.
While I’ve hand-waved over a broad and complex territory of detailed user journey mapping, remember, sending a business text is a deliberate action. By sending a text message, you’re sounding a bullhorn on their phone; make it worth their while.
Finally
There are two ways to build a culture of compliance, one punitive, and the other collaborative. The punitive approach is minimalistic, aiming merely to avoid regulatory trouble. It is typically adversarial to the ecosystem and disrespectful to the consumer. In contrast, the collaborative approach is expansive and expressive. It pays attention to the intent, content, and consent of the message, understanding that the best way to ensure compliance is to keep the customer in control and informed. This approach strives to embody the spirit of the law rather than quibbling over its letter. For instance, if a customer says ‘please take me off your list’, the response is to remove them first and ask questions later, rather than hiding behind excuses like “they didn’t respond with STOP.”
A true culture of compliance is a collaborative one and a tribute to long-termism. If you really want to create and retain a customer you will treat them like you would like to be treated. This may sound like flower child-speak, but it is the only way to build a sustainable enterprise. It is simple to grasp, but hard to execute.