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Let's be real, the statistics around SMS marketing are mind-blowing.
SMS boasts as high as a 98% open rate and 51% of consumers say they're more likely to make a purchase if they receive an SMS message that includes an ad, discount coupon, or QR code. Not surprisingly, many brands are rushing to adopt SMS marketing into their strategies, but after the dream stage, most companies awake to a harsh reality: The Twilio bill.
Unlike most traditional channels that marketing teams are used to working with (email, push notifications, in-app messaging, etc.), SMS messages aren't free. There's a cost associated with each message sent, and those costs add up.
But how can you reduce these costs while still preserving your messaging effectiveness?
Segmentation to save costs on SMS Messaging
If you're looking to save cost on your SMS messaging, segmentation is a great way to start. Let's walk through each of the four main types of segmentation and how you can effectively use them to reduce your cost while keeping your conversion rates high:
Geographic Segmentation — Only send to users who are in proximity
Geographic segmentation divides a target market into smaller groups based on location or region. While this type of segmentation may not necessarily be useful for some applications (e.g. eCommerce...unless you're selling season-specific clothing), only sending messages to those users who are in-range of your services can help take a huge chunk out of your SMS marketing bill.
A couple examples where geographic segmentation can be very helpful and useful at reducing SMS marketing expenses include food delivery apps, who should only send messages to users who are in-range of a particular restaurant's delivery radius, or two-sided marketplaces (like Uber) who need to connect specific drivers to specific riders at specific locations or within a certain range.
Not messaging people who aren't in range of your services may sound obvious, but it's easy to do and is a great first step towards reducing your SMS marketing bill.
Demographic Segmentation — Don't miss high value users
Demographic segmentation involves dividing a target market into smaller, more manageable groups based on specific demographic factors like age, gender, income, education level, occupation, marital status, ethnicity, religion, and family size, but despite most common advice, we would actually suggest NOT using demographic segmentation for your SMS messaging except for rare instances, as it has the potential to cut out your best users.
For example, a college or university might focus their marketing on potential students, aged 15 to 20, but this means they'd completely miss out on some higher-value segments like adults who may be considering continuing their education or pursuing more expensive degrees. Even in traditionally "gendered" areas like clothing or makeup, dividing audiences by gender may have a negative effect if individuals don't fit traditional gender roles or if one individual buys for an entire family.
Behavioral Segmentation — Send SMS messages to users based on events, activity levels, and consumption patterns
Behavioral segmentation is where you can start to make a huge dent in your SMS marketing bill. Behavioral segmentation is a marketing strategy that categorizes a target market based on their purchasing patterns, product usage, brand loyalty, and other behaviors related to their interactions with a product or service. Here are some examples of how you can use outputs from Behavioral segmentation to make your SMS marketing more effective:
- Frequency of Interaction: Send SMS promotions and updates more frequently to highly engaged customers who have a history of regularly interacting with your messages, while reducing the frequency for less active subscribers to save costs.
- Purchase History: Target customers who have a history of making high-value purchases with exclusive offers or upsell opportunities, while sending standard promotions to those with lower average order values.
- Abandoned Cart Reminders: Focus on sending SMS reminders to users who frequently abandon their shopping carts, encouraging them to complete their purchase and potentially recover lost sales.
- Re-Engagement Campaigns: Identify dormant subscribers who have not interacted with your SMS messages for a specified period and send re-engagement messages with special offers or incentives to revive their interest.
- Segment by Product Preferences: Tailor SMS campaigns based on customers' past product preferences or browsing behavior, ensuring they receive relevant and personalized offers that are more likely to lead to conversions.
The possibilities with Behavioral segmentation are vast, but the challenge is how to collect this data and identify these patterns manually.
Psychographic Segmentation — Send SMS messaging that more deeply resonates with your audience
The 'holy grail' of segmentation, psychographic segmentation involves categorizes a target audience based on their shared psychological traits, values, lifestyles, interests, and attitudes, allowing businesses to understand and target specific consumer motivations and preferences. Here are a few examples of how you can use psychographic segmentation to reduce your SMS costs:
- Interest-Based Offers: Tailor SMS promotions to specific interest groups, ensuring that each message resonates with the unique hobbies, passions, or activities of the recipients.
- Lifestyle-Centric Content: Create SMS content that aligns with the lifestyles, values, and attitudes of different segments, allowing for more personalized and effective messaging.
- Brand Advocates and Influencers: Identify and target segments of your audience who are more likely to be brand advocates or influencers, leveraging their enthusiasm to spread the word and potentially reduce marketing costs.
- Exclusive Membership Benefits: Offer exclusive SMS-only membership benefits or rewards to segments known for their loyalty and brand affinity, fostering stronger customer relationships.
- Behavioral Feedback Loops: Establish feedback mechanisms within SMS campaigns to gather insights on how different psychographic segments respond, allowing for continuous optimization and refinement of messaging strategies.
Similar to behavioral segmentation, true psychographic segmentation has traditionally been out of reach for most companies, as traditional methods for finding and building psychographic segments (surveys, customer focus groups, etc.) are costly, and it's hard to identify which new users fall into which psychographic segments before they've made their first transaction (not to mention all the work keeping up with all of these different segments entails)
That said, new forms of AI and Machine learning now allow you to extrapolate this information from your user data much more efficiently.
Identifying behavioral patterns with AI and machine learning
Mobile apps have a huge amount of data in the form of events. Any time a user does anything in an app, features like the user's ID, the event name, and a timestamp are recorded in the event stream.
Most times, though, businesses aren't using that data effectively. These events are typically only used to measure against, set triggers, or filter users. Most of them just live in your CDP like Amplitude, Segment, or Mixpanel, waiting to be queried.
Instead of just using these events mostly independently, we use AI to ingest all of an app's events and learn deep behavioral patterns through monitoring all of the user interactions in between these different events.
By monitoring all of your events for each user, we're able to surface patterns by user and then act on those patterns, adjusting messaging frequency, timing, and product recommendations based on predictive propensity scores gleaned from observing thousands of user interactions with each of these events.
Identifying psychographic preferences with AI and machine learning
Again, psychographic segmentation has traditionally been established by conducting expensive surveys and focus groups and this exercise is traditionally done separate from actual business outcomes (First, we try to understand what common threads our buyers have, and then we try to correlate this with business metrics).
This is where we've developed a novel approach to understanding user's psychographic preferences through messaging.
The process is simple:
- We construct thousands of messages, each uniquely appealing to different buyer psychographic preferences.
- Then we use a form of AI reinforcement learning with a very specifically-designed control group to understand, through each user's individual response (or lack of response) to messaging.
This has a few benefits. First of all, we're able to understand psychographic preferences before a user ever makes a purchase (They just need to click on a notification), and secondly, we're generating sales during the data collection process (not to mention the cost savings from not having to conduct focus groups, run surveys, etc.)
Here's a VP of data science at one of our customers explaining how they use our messaging as a 'micro-survey tool':
Bonus Tip: Learn on free channels, execute on SMS
User preferences aren't exactly the same between push notifications and SMS (e.g. some users don't want to be communicated with over SMS, while others prefer SMS over push notifications), but some user traits like behavioral and psychographic traits are consistent no matter the channel.
When should you use push notifications vs. SMS? No sweat. We have you covered.
By learning user behavioral and psychographic patterns on push notifications (as outlined above), and then transferring those learnings to SMS, you can start executing more efficient and effective SMS campaigns that effectively reduce your Twilio SMS marketing expense right out of the gate.
Bringing it all together — The results of AI-driven segmentation on SMS marketing effectiveness
By executing on each of these strategies (only messaging users within physical proximity, building on behavioral patterns, and appealing to psychographic interests), we're able to help customers maintain their messaging effectiveness while reducing their SMS costs by 75%.
You don't have to sacrifice your SMS marketing effectiveness to save costs. Using AI-driven segmentation (and learning on free channels) can help you both reduce costs and keep your conversions high.
Cover image by mamewmy on Freepik
