The Eight Reasons Your Triggered Messaging Doesn’t Work (in 2021)
Almost without exception, CRM marketers should look to make triggered messaging the core of what they do. These messages convert at a higher rate, create better customer experiences, and require less manual management than traditional campaigns.
What is a triggered message? Any message sent in response to a user’s action — typical examples include abandoned cart messages, newsletter registrations, and post-purchase upsell campaigns.
Despite this increased performance, though, not all triggered messaging is created equal. So how do you know if you’re leaving money on the table? Here are the eight biggest triggered messaging mistakes folks are making in the market today:
1. Your triggers aren’t coordinated/collide with the rest of your marketing & CRM activity.
If a customer is eligible for multiple campaigns, managing the underlying prioritization logic — and throttling the total number of campaigns sent — is challenging, if not impossible. This results in “trigger collisions.” Customers receive too many messages, many of which are conflicting, overlapping, or contradictory.
- Customers receive “abandoned cart” messages after purchasing an item.
- Customers receive a discount on an item they’ve already purchased at full price.
- Customers receive multiple messages within a few hours, all of which have different/disconnected calls-to-action.
- You have no control over where/when/to whom your triggered messages are sent.
- Auditing triggered message eligibility is difficult or even impossible.
Without triggered prioritization and integration, companies risk list disengagement. They will also suffer from lower revenue per send, and can take a significant hit to brand equity.
2. Your triggered content is one-size-fits-all.
You cannot effectively personalize the content of your triggered messaging based on what you know about the customer. Despite being very different from one another, customers receive messages that look identical.
- You cannot customize the products within an email to match the customer’s past browsing history, purchases, and recommended products.
- You cannot prioritize what’s shown in a message based on current inventory dynamics (e.g., price, availability).
- You cannot discount dynamically in a message based on a customer’s sensitivity to price (e.g., have they bought on discount? were they acquired on discount?).
- There’s a massive disparity between the personalization levels of your conventional versus triggered messaging.
Triggered content that isn’t meaningfully personalized creates a host of issues:
- It gives discounts to customers that don’t need them.
- It fails to leverage timely opportunities tied to inventory.
- And the messages themselves are less relevant, damaging your customer connection.
- The data bears this out: campaigns with > 2 in-message personalization elements drive 2x more clicks and 6x higher conversions.
3. Your triggers work independently across your channels, or you’re missing key channels.
You aren’t able to send coordinated triggered campaigns across all relevant customer engagement channels. In some cases, you’re unable to send triggered messages in a specific channel (e.g., push or SMS), or the triggers that you do send there are unsophisticated.
- You can’t send or manage triggered messaging in a specific channel (e.g., push).
- You can’t dynamically prioritize triggers based on expressed channel preference.
- You can’t coordinate one channel (e.g., email) with another (e.g., SMS).
- You don’t have visibility into customer journeys that stretch across channels.
- Your customers are receiving disconnected or duplicative messages across channels.
- Your customer engagement is lower in a specific domain (e.g., mobile).
Campaigns coordinated across channels simply work better. Significantly better.
- Conversion rates for campaigns that leverage a push AND an email action are 2.6x higher.
- Campaigns that effectively recruit 3+ channels can see returns well above this number.
4. Your triggered attribution models are way too vendor-friendly.
Some vendors have pushed revenue guarantees aggressively over the last few years, which can be very appealing from a contractual perspective. The problem is that — in most cases — the models they use to evaluate their own performance are deficient and ruthlessly self-interested.
These vendors “show incrementality” by refusing to agree to a real holdout and by drastically ramping send volumes. In effect, they’re simply cannibalizing other channels and taking credit.
- Your vendor guarantees a contract based on a flat percentage of topline revenue but refuses to agree to a proper control group to assess efficacy.
- Your provider charges a percentage of total digital revenue generated, and the number feels very high, but they’ve justified it by claiming incrementality.
- Your vendor has total control over the volume and content of sends, aggressively using discounts and increased send-volume to hit goals.
- Losses in other channels largely offset incremental gains in your vendor’s primary channel.
- Your vendor is justifying an investment in their platform via a reallocation of acquisition spend.
You’re wasting money and showing fake incrementality. These vendors have built businesses on the back of creative storytelling, strong sales processes, and basic triggering capabilities, but they should not be part of any modern marketing stack. Beyond the cost, their aggressive, discount-led sending approach tends to damage lists and erode margin. Not a great combination.
5. You can’t test your triggers in the same way that you test other aspects of your marketing.
Because they’re harder to build and harder to manage than standard campaigns, behavioral triggers can get short shrift when it comes to iteration. Merely getting the trigger out the door can be daunting enough. The associated workflow challenges mean that incremental experimentation simply doesn’t seem ROI positive. Additionally, understanding triggered campaigns’ performance is inherently more challenging due to conversions happening over an extended period instead of within a specific window.
- You don’t have multiple variants of your triggered campaigns running.
- You haven’t tested critical aspects of your triggered campaigns (e.g., send time, sub-segmentation, offer level, ordering) due to workflow/resource constraints.
- You lack the functionality to run meaningful experiments on your triggered messaging program.
- You don’t have a strong understanding of the deeper dynamics of your triggered messaging campaign performance beyond topline metrics (e.g., clicks, opens, sends).
- You believe there are incremental performance gains to be found in your triggered messaging program.
The data could not be more transparent: experimentation drives significant incrementality. Companies that don’t experiment are hemorrhaging opportunities. Across our customer base, experimentation drives upward of a 63% lift for behavioral triggers, and that value increases dramatically (to 3.5x) when looking at experiments with four or more variants tested. Workflow and resources are almost always the limiting factors, but companies don’t feel as if there are achievable solutions.
6. Your triggers are too slow and fail to get the attention of your customer.
Sending “real-time”/low-latency triggered campaigns remains a challenge for many brands. While campaigns entirely reliant on streaming data (e.g., abandonment) are typically easier to speed up, other types of lifecycle triggers are often still running on 12–48 hour windows. This latency has a meaningful impact on conversion metrics and represents a significant challenge, particularly for enterprise brands undergoing digital transformation.
- You have one or more lifecycle campaigns currently running on a latent (e.g., > 12 hours) trigger.
- You have collisions between conversion events and pre-purchase triggered campaigns (e.g., customers getting abandoned cart messages after buying).
- You don’t know the latency of specific lifecycle triggers or have gotten ad hoc feedback that people aren’t getting particular messages they’re eligible for.
- When building your triggered messaging strategy, you’re often forced to choose between message speed and depth of personalization.
- You currently use an older marketing cloud – e.g., SFMC, Responsys, or Adobe Campaign.
- You don’t have a centralized data warehouse or lack a centralized data science/data engineering function.
“Going real-time” is an important goal for marketers. Intuitively, they understand that being more responsive to the customer is likely to impact performance positively. And they’re right: low-latency behavioral triggers (i.e., < 1 hr) perform 100% better with no increase in unsubscribes. Bottom line: if you don’t have a strategy to get faster, start building one.
7. You aren’t able to adjust triggered logic using everything you know about the customer.
Determining who gets what is just as much a data problem as a strategic one. Companies collect a tremendous amount of data on their customers but often struggle to use it in a marketing context. Triggered campaigns are no exception: data integration and storage issues with modern martech solutions frequently prevent the full customer record from being leveraged. As a result, key data points often go unused, reducing the scope of personalization and capping possible performance gains.
- You can’t use certain data types (e.g., browsing data, customer support interactions) to sub-segment or adjust triggered messaging.
- You can’t suppress customers from triggers based on key profile attributes (e.g., high-value customers, new customers).
- One or more customer data sources remain unconnected to your marketing cloud/triggered marketing provider.
- Your triggered messaging campaigns feel “basic” or “uninspired.”
- You get customer feedback about triggered messaging being inappropriate/incorrectly targeted.
- Your CRM team has ideas for campaigns that they’re unable to implement due to data-availability issues.
- You struggle to use historical data points alongside real-time streaming data when you design a triggered campaign.
Recruiting more data sources leads to better campaigns: lift from campaigns that use data from 2+ sources is 1.1x higher than those only using a single data source.
8. Your triggers are single-step.
You run triggered campaigns, but they’re not “journeys” — they’re one-and-done. Triggered campaigns work because they respond to moments of high customer intent; a single message often represents only a fraction of the possible engagement a marketer might drive.
- You don’t have multi-step campaigns for your primary triggered touchpoints (e.g., abandonment).
- You’ve tapped out specific messaging moments’ performance but haven’t explored extending those moments with incremental messages.
- Your CRM team tends to think in terms of specific message performance, not sequence/journey performance.
- You suspect you could find incrementality in extending messaging sequences or building more complex journeys, but you’re resource/workflow constrained.
This is often the single biggest leverage point for CRM teams looking to improve their triggered messaging programs. Customers have been known to respond to the third, fourth, fifth, or even sixth message in a journey, particularly where considered purchases are concerned. For example, conversion rates for triggered abandonment journeys are up to 3x higher, with a 24% higher open rate than single messages.
You can’t afford to settle for mediocrity when it comes to your triggered messaging. Companies addressing all 8 of these challenges are winning market share, driving LTV, realizing outsized performance gains, and setting themselves up for the future. Companies that fail to embrace them are leaving money on the table. It’s that simple. And while “simple” doesn’t necessarily mean “easy,” all of this is possible for any business with the right strategy, data infrastructure, and technology partners in place.
If the promise of flexible, scalable first-party data paired with cross-channel execution and automated personalization sounds exciting, then check out How Self-Serve Segmentation Led to a 300x Boost in Engagement to see how one of Simon Data’s clients has been able to dominate the market with marketing-owned data strategies.