The speed at which you see your ad performance data directly determines how fast you can optimize. A brand that sees yesterday's attribution data at 9 AM today can make budget adjustments by 10 AM. A brand that sees attribution data with a 48-hour delay is spending money on underperforming campaigns for two extra days before catching the problem. In high-spend environments where daily budgets run into thousands or tens of thousands of dollars, those extra days of delayed data translate directly into wasted budget. This is the core problem that Cometly solves: real-time attribution data that lets you react within hours, not days.
Cometly and Inflowave address two different but connected challenges for DTC brands and agencies. Cometly is a real-time ad attribution platform that uses server-side tracking to show you which ads are driving conversions as they happen. It works despite iOS privacy restrictions, ad blockers, and cookie limitations because the tracking happens on your server, not in the browser. Its Conversions API integrations feed attribution data back to ad platforms like Facebook, Google, and TikTok for better optimization. Its multi-touch attribution models assign credit across the full customer journey, not just the last click. Inflowave is the Instagram CRM and engagement platform that captures the conversion path most attribution tools miss entirely: the DM conversation. When a customer sees your ad, visits your Instagram profile, and sends a DM to ask about your product before buying, that conversation is invisible to Cometly's server-side tracking. But it might be the conversation that determined whether they purchased or not.
Together, Cometly and Inflowave give brands a complete revenue picture in real time. Cometly shows the direct conversion path: ad click to website visit to purchase. Inflowave shows the conversation conversion path: ad view to Instagram DM to qualification to deal close. For many DTC brands, especially those selling premium, customizable, or complex products, the conversation path represents 20% to 40% of total ad-attributed revenue. Without both tools, you are making real-time optimization decisions based on incomplete data. With both, every budget decision accounts for the full revenue your ads generate, through both the checkout page and the DM inbox.
What Cometly actually does (and why speed matters for attribution)
Cometly was built with a specific thesis: accurate attribution data is only useful if you receive it fast enough to act on it. Most attribution platforms process data in batches, meaning you see today's performance data tomorrow morning or, in some cases, two days later. Cometly processes attribution data in real time, streaming conversion events from your server to your dashboard as they happen. This real-time architecture is not just a nice feature. It fundamentally changes how media buyers operate. Instead of making optimization decisions based on yesterday's data, you make decisions based on what is happening right now. This shift from reactive to proactive optimization is especially valuable for brands running time-sensitive campaigns, product launches, or promotions where every hour of misallocated budget matters.
Server-side tracking - Attribution that works in a privacy-first world
Cometly's server-side tracking is the technical foundation that makes accurate, real-time attribution possible. Instead of relying on a JavaScript pixel in the user's browser to capture conversion events, Cometly captures events on your server. When a customer makes a purchase on your website, your server sends the conversion event directly to Cometly's servers with all the associated data: the click ID, the customer identifier, the order amount, and the product details. This server-to-server communication bypasses every obstacle that has degraded browser-based tracking in recent years: ad blockers that block tracking scripts, iOS App Tracking Transparency that prevents cross-site tracking, browser privacy features that delete or restrict cookies, and VPNs that obscure user identity.
The practical difference between server-side and browser-based tracking is significant for attribution accuracy. Studies estimate that browser-based pixels miss 20% to 40% of conversion events due to ad blockers, cookie restrictions, and privacy settings. That means a campaign that actually drove 100 conversions might only show 60 to 80 in your pixel-based attribution. You are making budget decisions based on incomplete data and, worse, you do not know which specific conversions are missing. Cometly's server-side approach captures 95% or more of conversion events because the tracking happens on your own server infrastructure where privacy tools cannot interfere. For brands spending tens of thousands of dollars per month on ads, the difference between tracking 60% of conversions and tracking 95% of conversions can completely change which campaigns appear profitable and which appear to be losing money.
Conversions API (CAPI) integration - Feed better data back to ad platforms
Cometly integrates natively with the Conversions APIs of major ad platforms: Facebook/Instagram (Meta CAPI), Google (Enhanced Conversions), TikTok (Events API), and Snapchat. These integrations send your server-side conversion data back to the ad platforms, which use it to optimize their delivery algorithms. When Facebook's algorithm knows exactly which ad clicks led to purchases (with high confidence, server-side data), it can find more people likely to convert, resulting in lower cost per acquisition. Without CAPI data, Facebook's algorithm relies on its own pixel data, which is increasingly incomplete due to iOS privacy restrictions.
The CAPI integration creates a virtuous cycle: better conversion data leads to better algorithmic optimization, which leads to lower CPAs, which leads to more efficient campaigns, which generates more conversion data. Brands that implement Cometly's CAPI integration typically see a 15% to 30% reduction in CPA within 2 to 4 weeks as the ad platforms' algorithms learn from the more complete conversion data. For Instagram ad campaigns specifically, the CAPI integration is particularly valuable because Instagram ads run through Meta's advertising system, and Meta's optimization algorithm is the same for both Facebook and Instagram. Better CAPI data improves optimization across both placements simultaneously. When combined with Inflowave's DM pipeline data, you can also identify ads that drive DM conversations (tracked by Inflowave) but do not generate direct website purchases (tracked by Cometly), giving you a more complete picture of which ads actually drive business value.
Multi-touch attribution models - See the full journey, not just the last click
Cometly supports multiple attribution models that let you analyze the customer journey from different perspectives. The last-click model credits the final touchpoint before purchase, which is the simplest but often the most misleading because it ignores all the awareness and consideration touches that brought the customer to the point of purchase. The first-click model credits the initial discovery touchpoint, which captures acquisition channels but ignores the nurturing that happened after. The linear model distributes credit equally across all touchpoints, providing a balanced view but treating a casual ad impression the same as a high-intent click. Cometly also offers data-driven attribution that uses your actual conversion data to weight touchpoints based on their influence on the purchase decision.
The ability to compare attribution models side by side is crucial for making informed budget decisions. An Instagram campaign might look mediocre in last-click attribution because many Instagram-initiated journeys end with a direct website visit or a Google search (where the customer types your brand name). In those cases, "direct" or "search" gets the credit even though Instagram started the journey. In first-click attribution, the same Instagram campaign looks much stronger because it gets credit for all the journeys it initiated. In Cometly's data-driven model, Instagram typically gets proportional credit based on its actual influence, which usually falls between the conservative last-click number and the generous first-click number. Layering Inflowave's DM pipeline data on top of any of these models adds the conversation-driven conversions that none of the attribution models capture, because those conversions happen in Instagram DMs, not on tracked web pages.
Real-time dashboards - Make decisions today based on today's data
Cometly's dashboards update in real time, showing attributed revenue, ROAS, CPA, and conversion counts as events stream in throughout the day. The dashboard is organized for quick decision-making: a top-level summary shows total spend and revenue across all channels, and you can drill down to the ad account level, campaign level, ad set level, and individual ad level in a few clicks. Filters let you isolate specific date ranges, channels, attribution models, and product categories. For brands running time-sensitive promotions or product launches, this real-time visibility means you can see which launch-day ads are converting within the first hour and shift budget to winners before the day is over.
The real-time aspect becomes especially powerful when paired with Inflowave's real-time DM monitoring. When you launch a new ad campaign, Cometly shows you within hours which ads are driving website conversions. Simultaneously, Inflowave shows you which ads are driving DM conversations. Sometimes these two signals align: an ad that drives strong website conversions also drives lots of DMs. Other times, they diverge: an ad might drive minimal website purchases but generate a flood of DM conversations where prospects ask detailed questions before buying. Without both tools, you would see only the Cometly data, conclude that the second ad is underperforming, and potentially pause it. With Inflowave's data, you see that the second ad is actually driving significant pipeline revenue through conversations. This real-time dual visibility prevents premature optimization decisions that would kill campaigns with hidden value.
Cookieless tracking and identity resolution - Future-proof your attribution
As the digital advertising industry moves toward a cookieless future, Cometly's architecture is built to thrive in that environment. Because the core tracking mechanism is server-side rather than cookie-based, attribution accuracy does not degrade as browsers restrict cookies further. Cometly's identity resolution engine matches conversions to ad clicks using first-party data signals including email addresses, phone numbers, and customer identifiers that your server sends with each conversion event. This first-party matching is more reliable than third-party cookie matching and is fully compliant with privacy regulations because you are using your own customer data, not data collected by third-party trackers.
The identity resolution works across devices and sessions. A customer who clicks your Instagram ad on their phone, browses your website on a laptop later that day, and purchases from a tablet the next morning can be matched across all three touchpoints if they use the same email address or phone number at any point in the journey. This cross-device matching is critical for accurate attribution in a world where the average customer uses 3 to 4 devices. For brands that collect email addresses or phone numbers through Inflowave's AI chatbot during DM conversations, there is an additional benefit: the customer identity captured in the DM can potentially be matched to their website browsing behavior tracked by Cometly, creating an even more complete picture of the customer journey from ad exposure through DM conversation through website purchase.
What Inflowave brings to the equation
Cometly tracks conversions that happen on your website. Inflowave tracks conversions that happen through Instagram conversations. For DTC brands where Instagram is both an advertising channel and a customer service channel, a meaningful percentage of sales involve a conversation before a purchase. The customer sees an ad, has a question, sends a DM, gets an answer, and then buys. Cometly captures the purchase. Inflowave captures the conversation that influenced the purchase. Without both, you are attributing revenue but missing the engagement that drove it.
Instagram CRM - Track the conversation layer that attribution tools miss
Inflowave's Instagram CRM captures every DM conversation across all your Instagram accounts and organizes them in a unified inbox. Each conversation is tagged with its source: did this person arrive from an ad, a story reply, a comment, an organic profile visit, or a shared post? For conversations triggered by ads, the specific campaign and ad creative are captured when identifiable through UTM parameters or referral signals. This source attribution creates a direct link between Cometly's ad cost data and Inflowave's conversation outcome data. You can trace a specific closed deal in Inflowave's pipeline back to a specific ad campaign that Cometly is also tracking, and compare the revenue picture from both perspectives.
The CRM tracks every message, timestamp, team member interaction, and lead status change in the conversation history. For brands where DM conversations influence purchasing decisions, this conversation data is as valuable as website analytics data. You can see which questions customers ask most frequently (which informs your ad copy and landing page content), how long the average conversation lasts before the customer purchases (which informs your response time SLAs), and which team members have the highest DM-to-purchase conversion rates (which informs staffing and training decisions). These insights are completely invisible to Cometly because they happen inside Instagram's messaging system, but they directly impact the conversion rates that Cometly tracks.
AI chatbot and automation - Convert ad traffic at scale without adding headcount
When your Cometly-tracked ads are driving strong performance and you increase budget, the resulting increase in Instagram DM volume can quickly overwhelm human teams. An ad campaign that generates 50 DMs per day at a $2,000 daily budget will generate 150 DMs per day when you scale to $6,000. Without automation, you need to triple your response team to maintain the same response speed and quality. Inflowave's AI chatbot scales automatically. It handles 50 or 500 DMs per day with the same response speed (under 15 seconds) and the same quality (trained on your specific product and brand voice). This means you can scale ad spend aggressively based on Cometly's real-time performance data without worrying about whether your DM team can keep up.
The chatbot also enables a specific ad strategy that is particularly effective for DTC brands: the "DM us" CTA. Instead of sending all ad traffic to a product page, you run ads with CTAs like "DM us for 15% off" or "DM us for custom sizing help." These ads often produce higher engagement rates because they promise a personalized interaction rather than a generic shopping experience. The chatbot handles the resulting DM volume, delivers the promised value (discount code, sizing help, product recommendation), and qualifies the prospect for a purchase. Cometly tracks the eventual website purchase that follows the DM conversation, and Inflowave tracks the conversation that made the purchase happen. Together, you see both the ad's direct conversion rate (Cometly) and the ad's conversation-assisted conversion rate (Inflowave), giving you a complete picture of each ad's true effectiveness.
Sales pipeline - Revenue attribution from conversation to close
Inflowave's visual pipeline tracks every DM lead through your sales process with revenue attributed at the deal level. For DTC brands, the pipeline stages might be: Inquiry (customer asked about a product), Matched (you recommended a specific product), Quote Sent (shared pricing or a link), Purchased (deal closed), or Lost (customer did not buy). Each stage captures the lead's progression and the factors that influenced the outcome. Revenue recorded against won deals is attributed to the campaign source, creating a revenue dataset that complements Cometly's website conversion revenue.
The pipeline data reveals patterns that Cometly's attribution cannot. You might discover that customers who DM about product A have a 45% close rate but customers who DM about product B have only a 12% close rate, even though both products have similar website conversion rates. This indicates that product B needs better information on the website (so customers can self-serve without needing a DM conversation) while product A benefits from the personal touch (the DM conversation adds value that increases conversion). These product-level conversation insights, available only in Inflowave's pipeline data, inform both ad creative strategy (which products to feature in "DM us" ads versus "Shop now" ads) and website optimization (which product pages need better FAQ sections to reduce unnecessary DM inquiries).
Content scheduling and engagement analytics - Build the Instagram presence that converts
Cometly tracks how your ads perform. Inflowave tracks how your overall Instagram presence supports those ads. An Instagram profile with regular, high-quality content, active stories, and engaged followers converts ad traffic at significantly higher rates than a sparse profile with infrequent posts. Inflowave's content scheduling lets you maintain a consistent organic posting schedule across all your Instagram accounts, ensuring that when paid traffic arrives, they see an active, trustworthy brand presence that reinforces the ad's message.
Inflowave's engagement analytics show how organic content performance correlates with paid ad performance. You can see whether weeks with more organic posting correspond to higher DM conversation rates from ads, whether specific types of content (customer testimonials, behind-the-scenes, product demos) increase the conversion rate of DM conversations, and whether higher engagement rates on organic posts lead to lower CPAs in Cometly. These correlations help you optimize the entire Instagram ecosystem, not just the ads in isolation. For brands and agencies that manage both organic and paid Instagram presence, this holistic view ensures that organic content strategy supports and amplifies the paid advertising strategy tracked by Cometly, rather than operating as a disconnected activity.
The five-step workflow: from real-time data to total revenue optimization
Here is how DTC brands and agencies structure their attribution and engagement workflow when using Cometly for real-time ad tracking and Inflowave for Instagram CRM. The defining characteristic of this workflow is speed: Cometly provides real-time attribution data, and Inflowave provides real-time DM engagement data. Together, they enable optimization decisions within hours of campaign launch rather than days, which compounds into significant budget savings and revenue gains over time.
Step 1: Set up Cometly server-side tracking and CAPI integrations (Day 1)
Install Cometly's server-side tracking pixel on your website and connect your ad accounts from Meta, Google, TikTok, and any other platforms you advertise on. The installation process is straightforward and typically takes 15 to 30 minutes for a standard e-commerce setup. Once installed, Cometly begins capturing conversion events in real time. Configure your CAPI integrations so that conversion data flows back to each ad platform's optimization algorithm. Set up your attribution models (last-click, first-click, linear, and data-driven) so you can compare how each model attributes revenue to your campaigns. Create a dashboard layout that gives you a quick view of spend, revenue, ROAS, and CPA across all channels.
During the first 24 to 48 hours, validate that Cometly is tracking conversions accurately by comparing its numbers against your e-commerce platform's order data. The numbers should be close, with Cometly potentially showing slightly more attributed conversions than your platform's built-in analytics because server-side tracking captures events that browser-based tracking misses. If the numbers diverge significantly, check your implementation for issues with the server-side event format or customer identifier matching. Once validated, Cometly becomes your source of truth for ad attribution, replacing the self-reported numbers from ad platforms that tend to over-count conversions.
Step 2: Configure Inflowave to capture ad-driven DM conversations (Day 1-2)
Connect your Instagram accounts to Inflowave and set up the AI chatbot for each account. Configure the chatbot with your product catalog, frequently asked questions, brand voice guidelines, and qualification criteria. Set up your lead pipeline stages to match your DM sales process. Create auto-tagging rules that identify DM conversations originating from ads (using UTM parameters, referral patterns, or keyword triggers in the initial message). Configure workflow automations for follow-up sequences so no lead goes cold after the initial conversation.
Test the complete flow by clicking through one of your own ads, sending a DM, and verifying that the chatbot responds appropriately, the lead is created in the pipeline with the correct source tag, and the follow-up workflows trigger as expected. This end-to-end test ensures that when real ad traffic arrives, every DM conversation is captured, attributed, and managed systematically. Pay special attention to the chatbot's handling of product-specific questions. If you sell multiple product categories, the chatbot should be able to identify which product the customer is asking about and provide relevant information without generic responses that feel impersonal.
Step 3: Launch campaigns and monitor both data streams in real time (Week 1)
Launch your ad campaigns and monitor performance simultaneously in both Cometly and Inflowave. In Cometly, watch for real-time ROAS, CPA, and conversion volume by ad. Identify which ads are driving website purchases within the first few hours of launch. In Inflowave, watch for DM volume by source, chatbot engagement rates, and pipeline progression. The goal during the first week is to identify the relationship between Cometly's website conversion data and Inflowave's DM engagement data for each campaign. Some campaigns will drive both website purchases and DM conversations. Others will drive one but not the other. Understanding this relationship for each campaign is the key insight that determines your optimization strategy.
Set up a daily review routine where you check both dashboards side by side each morning. Cometly's real-time data tells you which ads drove purchases overnight. Inflowave's pipeline tells you which ads drove DM conversations overnight. Cross-referencing these two data streams reveals ads with "hidden value." An ad that shows a modest 2x ROAS in Cometly might be generating 25 DM conversations per day in Inflowave, where 30% convert into purchases at a higher AOV than the direct website path. That ad's true ROAS, accounting for both direct and conversation-assisted purchases, might be 3.5x or higher. Without the Inflowave data, you might pause it. With it, you scale it.
Step 4: Calculate total ROAS per ad using both data sources (Weekly)
Each week, build a combined ROAS report that includes both Cometly-attributed website revenue and Inflowave-attributed DM pipeline revenue for every ad. The formula is straightforward: Total ROAS = (Cometly website revenue + Inflowave pipeline revenue) / Ad spend. This total ROAS number is a more accurate representation of each ad's value than either tool's number alone. For some ads, Inflowave pipeline revenue adds 5% to the total. For others, it adds 40% or more. The ads with the largest Inflowave contributions are typically those with strong engagement hooks, product complexity that requires conversation, or audiences that prefer personal interaction before purchasing.
Use the combined data to make optimization decisions. Ads with high total ROAS (website plus DM revenue) deserve more budget, even if their Cometly-only ROAS looks mediocre. Ads with high Cometly ROAS but zero DM revenue are efficient direct response ads that can be scaled without DM management overhead. Ads with zero Cometly ROAS but significant DM pipeline revenue need the chatbot and follow-up workflows to be running well, because their entire value depends on the conversation path. This categorization helps you manage your Instagram strategy holistically: some ads are designed to drive direct purchases, some are designed to drive conversations, and your total revenue comes from optimizing both types.
Step 5: Scale winners and test "DM us" CTAs vs "Shop now" CTAs (Ongoing)
With combined data from Cometly and Inflowave, you can now run one of the most valuable tests in DTC advertising: comparing "DM us" CTAs against "Shop now" CTAs on the same products. Create two versions of the same ad, one that sends traffic directly to your product page (tracked by Cometly) and one that invites people to DM you for a personalized recommendation or discount (tracked by Inflowave). Run both versions with equal budget and compare total revenue after 2 to 4 weeks. For many products, especially those with sizing questions, customization options, or premium price points, the "DM us" version generates higher total revenue because the conversation builds trust and removes purchase hesitation.
Scale your winners based on total ROAS, not just direct conversion metrics. Use Cometly's CAPI integration to feed back the conversation-assisted conversion data to Meta's algorithm (by firing a conversion event when a DM lead makes a purchase), so the algorithm learns to find more people who are likely to both click and engage in a conversation. Set up Inflowave workflows that automatically send purchase links to qualified DM leads, track click-through and purchase rates on those links, and fire the CAPI conversion event when the purchase completes. This creates a fully instrumented funnel where every step from ad impression through DM conversation through purchase is tracked, attributed, and fed back into the optimization algorithm.
Real use cases for DTC brands and agencies
Premium DTC brand with customizable products
A jewelry brand selling customizable pieces (engraved rings, personalized necklaces, birthstone bracelets) with an average order value of $180 to $320 uses Instagram as a primary sales channel. Most customers have questions about customization options, metal types, sizing, and engraving before purchasing. The brand runs Instagram and Facebook ads with a mix of "Shop now" and "DM us for a custom quote" CTAs. Cometly tracks the direct website purchases from "Shop now" ads, showing a 2.8x ROAS. Inflowave tracks the DM conversations from "DM us" ads, where the AI chatbot helps customers choose their customization options and sends them a personalized product link when they are ready to purchase.
When the brand combined Cometly and Inflowave data, they discovered that "DM us" ads had a total ROAS of 4.2x (versus 2.8x for "Shop now" ads) because the conversation path produced higher average order values ($285 vs $195) and significantly lower return rates (4% vs 18%). Customers who received personalized guidance through the chatbot chose products that matched their expectations, while customers who purchased directly from the website were more likely to receive a product that did not match their imagined specifications. Based on this data, the brand shifted 60% of their ad budget to "DM us" campaigns and trained the chatbot to handle the most common customization questions. Monthly revenue increased by 35% while return rates dropped from 14% overall to 8%, creating a double improvement in profitability.
Skincare brand with a product recommendation funnel
A skincare brand with 12 products across 3 skin types (oily, dry, combination) uses Instagram ads to drive both direct purchases and "skin quiz" DM conversations where the AI chatbot asks about skin concerns, current routine, and goals, then recommends a personalized product bundle. Cometly tracks direct website purchases, showing which ads drive the most conversions on the product pages. Inflowave tracks the "skin quiz" DM conversations, where the chatbot builds a personalized bundle recommendation based on the customer's answers and sends a checkout link for the recommended bundle.
The combined data revealed two important findings. First, the DM-recommended bundles had a 2.3x higher average order value ($92 vs $40) because the chatbot recommended complementary products that customers would not have discovered on their own. A customer who visited the website might buy a single moisturizer for $40, but a customer who went through the chatbot quiz typically purchased a moisturizer, cleanser, and serum bundle for $92. Second, customers who went through the chatbot quiz had a 40% higher 90-day repurchase rate because the personalized recommendation matched their actual needs, increasing satisfaction and retention. Cometly's data showed which ads drove the cheapest direct purchases. Inflowave's data showed which ads drove the most valuable customer relationships. The brand optimized for the latter and saw lifetime customer value increase by 55% within 6 months.
DTC agency managing 10 brands with real-time reporting needs
A DTC agency managing 10 brand accounts with a combined monthly ad spend of $200,000 uses Cometly as their central attribution platform and Inflowave as their Instagram engagement platform. The agency's value proposition to clients is real-time performance visibility and rapid optimization, which requires both tools working together. Cometly provides real-time ROAS dashboards for each client, and Inflowave provides real-time DM engagement dashboards. The agency's daily standup meeting reviews both datasets for every client: which campaigns are winning in Cometly, which campaigns are driving DM conversations in Inflowave, and where the two data streams tell different stories that warrant investigation.
The agency discovered that presenting "total ROAS" (Cometly website revenue + Inflowave pipeline revenue) during client calls significantly improved client retention. Previously, clients would compare the agency's reported ROAS (from their previous attribution tool, which only tracked website conversions) against their actual revenue in Shopify and notice a gap. The gap was DM-sourced revenue that the agency was generating through Instagram but could not attribute. With Cometly and Inflowave combined, the agency could show that the "missing" revenue came from DM conversations their ads generated. For three clients where DM revenue exceeded 30% of total ad-attributed revenue, this data prevented cancellations because the clients finally understood the full impact of their Instagram investment. The agency now includes "total ROAS" as a standard metric in every client report, with a clear breakdown showing Cometly-attributed direct revenue and Inflowave-attributed conversation revenue.
Frequently Asked Questions
What is Cometly and how does it differ from Facebook Ads Manager reporting?
Cometly is an independent ad attribution platform that uses server-side tracking to show you which ads drive conversions in real time. Unlike Facebook Ads Manager, which uses its own attribution model that naturally credits Facebook for as many conversions as possible, Cometly provides an independent, third-party view of your ad performance. This independence is important because Facebook tends to over-report conversions due to its self-serving attribution model and the increasing difficulty of browser-based tracking. Cometly's server-side approach captures more conversions than pixel-based tracking and attributes them more accurately because it is not biased toward any single ad platform.
How much does Cometly cost?
Cometly offers tiered pricing that typically starts around $199 per month for smaller brands and scales based on your monthly ad spend and feature needs. Higher-tier plans include advanced attribution models, more ad account connections, team collaboration features, and priority support. Cometly positions itself as a cost-effective alternative to more expensive attribution platforms like Hyros, offering comparable server-side tracking accuracy at a lower price point. For most brands spending $5,000 or more per month on ads, the subscription pays for itself if it helps identify and cut even one underperforming campaign or scale one hidden winner. Check their website for the most current pricing.
Is Cometly better than Hyros?
Cometly and Hyros both offer server-side ad attribution, but they differ in positioning, features, and pricing. Cometly emphasizes real-time data delivery, ease of setup, and competitive pricing, making it accessible to a wider range of brands. Hyros tends to target higher-spend advertisers with advanced features like AI-powered ad optimization, deep call tracking, and long attribution windows. Cometly is often favored by brands that want accurate, real-time attribution without the complexity and higher price point of Hyros. The best choice depends on your budget, ad spend level, and whether you need Hyros's advanced optimization features or prefer Cometly's focus on speed and simplicity.
Does Cometly track Instagram DM sales?
Cometly tracks Instagram ads through its Meta Ads integration and attributes conversions that happen on your website, including purchases made by customers who clicked on Instagram ads. However, Cometly does not track conversations or sales that happen inside Instagram DMs because those interactions do not generate server-side events on your website. This is the specific gap that Inflowave fills. Inflowave captures the DM conversation, qualifies the lead, tracks the pipeline progression, and records revenue when the deal closes. Together, Cometly shows the direct conversion path and Inflowave shows the conversation-assisted conversion path.
What is server-side tracking and why is it better than pixel-based tracking?
Server-side tracking sends conversion data from your server directly to the attribution platform (in this case, Cometly) rather than relying on a JavaScript pixel in the user's browser. Pixel-based tracking is increasingly unreliable because ad blockers block tracking scripts, iOS privacy settings prevent cross-site tracking, browsers are restricting third-party cookies, and VPNs can obscure user identity. Server-side tracking bypasses all of these issues because the data transmission happens between servers, not through the browser. The result is significantly higher conversion capture rates, with server-side tracking typically capturing 95% or more of conversions versus 60% to 80% for pixel-based tracking alone.
How does Cometly compare to Triple Whale?
Cometly focuses on real-time attribution speed and server-side tracking accuracy across multiple ad platforms, positioning itself as a platform-agnostic attribution tool. Triple Whale offers a broader e-commerce analytics suite with deep Shopify integration, including LTV analytics, creative reporting, Moby AI recommendations, and Sonar enrichment automations. Cometly tends to be more affordable and faster to set up, while Triple Whale is more feature-rich for Shopify-centric DTC brands. Both solve the core problem of accurate ad attribution, and the choice often depends on whether you prioritize real-time data speed (Cometly) or deep e-commerce ecosystem features (Triple Whale).
Does Cometly support Facebook Conversions API (CAPI)?
Yes, Cometly integrates natively with Meta's Conversions API to send server-side conversion events back to Facebook and Instagram's optimization algorithms. This integration improves your ad performance because Meta receives more complete and accurate conversion data, which helps its algorithm find better audiences, improve delivery optimization, and reduce your cost per acquisition. The CAPI integration also works for Instagram ads since they run through the same Meta advertising system. Cometly handles the technical setup of CAPI event matching and deduplication, so you do not need to manage the API integration manually.
Can Cometly track offline or phone conversions?
Cometly primarily tracks online conversions through its server-side pixel and API integrations. For offline conversions like phone orders, in-store purchases, or bank transfers, you would need to send those conversion events to Cometly through their API, mapping them back to the original ad click using customer identifiers such as email addresses or phone numbers. This requires some technical setup but allows you to attribute offline revenue to the ads that initiated the customer journey. For brands that sell through multiple channels, this offline attribution capability ensures your total ROAS calculation accounts for all revenue, not just online purchases.
How accurate is Cometly compared to ad platform reporting?
Cometly typically shows more accurate numbers than ad platform reporting because it uses server-side first-party tracking that is not affected by ad blockers, iOS opt-outs, or cookie restrictions. Ad platforms like Facebook and Google tend to over-report conversions because they use attribution models that credit themselves generously and because their pixel-based tracking misses conversions from users with ad blockers or strict privacy settings. Most Cometly users report that the platform's numbers fall between the inflated numbers ad platforms report and the conservative numbers from last-click models, providing a more realistic view of true ad performance that more closely matches actual revenue in their e-commerce platform.
Do I need both Cometly and Inflowave, or can I use just one?
You can use each tool independently. Cometly is valuable on its own for any brand that runs paid ads and needs accurate, real-time attribution data, regardless of whether Instagram DMs are part of your sales process. Inflowave is valuable on its own for any business that uses Instagram as a communication or sales channel, regardless of whether you need advanced attribution. The combination becomes especially powerful for DTC brands where Instagram is both an advertising channel and a conversation-driven sales channel. If a meaningful percentage of your customers DM you before purchasing, or if you run ads with "DM us" CTAs, the combination reveals total revenue that each tool misses on its own and enables optimization decisions based on the complete picture.