Marketing Software Resources - Page 20

Articles and Discussions to expand your knowledge on Marketing Software

Resource pages are designed to give you a cross-section of information we have on specific categories. You'll find articles from our experts and discussions from users like you.

Contents

Marketing Software Articles

60+ Marketing Automation Statistics for 2027: ROI and Challenges

TL;DR: Key marketing automation statistics for 2027 How fast is the marketing automation market growing? The market is forecast to grow from $8.14 billion in 2026 to $20.12 billion by 2034. Are companies getting full value from marketing automation? 60% of B2B marketers say they are not using their existing tools to full capacity. How is AI changing marketing automation? AI and machine learning now account for 24.2% of marketing activity, up from 13.1% in 2024. Does personalization improve marketing results? 93.2% of marketers say personalized or segmented experiences led to more leads and purchases. How effective are automated emails? Behavior-based automated emails generated 30% of email revenue from just 2% of sends. How quickly does marketing automation pay back? G2 Data puts the estimated average payback period at 10 months. How long does marketing automation take to implement? In G2 Data, 83% of products go live within three months.

by Amita Jain

80+ Marketing Statistics to Shape Your 2026 Marketing Strategy

Marketing has always changed shape with its channels, but the shift underway in 2026 is different in kind. The marketing statistics that mattered two years ago described a discipline organized around search traffic, social reach, and email lists, with budgets allocated accordingly.

by Darshayita Thakur

2023 Trends: Making Your Marketing Win in Times of Loss

This post is part of G2's 2023 digital trends series. Read more about G2’s perspective on digital transformation trends in an introduction from Emily Malis Greathouse, director, market research, and additional coverage on trends identified by G2’s analysts.

by Victoria Blackwell

Marketing Software Discussions

Which Digital Analytics tools allow easy export of cohorts to marketing platforms and integration with data warehouses?

Which Digital Analytics tools allow easy export of cohorts to marketing platforms and integration with data warehouses matters a lot once a growth or marketing team wants to act on the same behavioral data the product team is already looking at. Mixpanel, Heap by Contentsquare, and Adobe Analytics are the three most cited for this kind of data portability.

Mixpanel: supports exporting defined cohorts directly to common marketing and ad platforms.
Heap by Contentsquare: integrates with data warehouses like Snowflake and BigQuery for teams that want raw event data alongside cohort exports.
Adobe Analytics: built for enterprise-scale integration across the broader Adobe marketing stack.
SAP Engagement Cloud (formerly SAP Emarsys): ties analytics data directly into marketing automation for teams already on SAP's stack.
Semrush: exports audience and traffic data that can feed into broader marketing workflows.

Has a cohort export ever broken or gone stale between your analytics tool and your data warehouse, and how did you catch it?

From what I've heard, a stale cohort export tends to get caught by the marketing side first, not the analytics side, someone notices a campaign is targeting people who converted weeks ago or excludes people who should qualify now, and that's usually the tell that the sync stopped refreshing rather than any alert firing on the data pipeline itself. That lag is exactly what makes it dangerous, the export doesn't fail loudly, it just quietly goes stale until the output looks off enough for someone to question it.

Answered: Mahima Chavan on September 17, 2026

What's the best Digital Analytics software for product managers at tech startups analyzing user behavior and feature adoption?

I've been researching what's the best Digital Analytics software for product managers at tech startups analyzing user behavior and feature adoption, since generic web analytics tools tend to fall short once a PM actually needs to see which features are sticking and which are getting ignored. Mixpanel, Heap by Contentsquare, and Amplitude-style product analytics come up most for this exact use case.

Mixpanel: built around event tracking and funnels, which maps directly onto feature adoption questions rather than generic pageview data.
Heap by Contentsquare: captures every interaction automatically, useful for startups that don't want to define every tracked event upfront.
Kissmetrics: focused on behavior and cohort analysis rather than raw traffic reporting.
Appier AIRIS (formerly Woopra): ties user journeys together across touchpoints, useful for understanding adoption paths.
Google Analytics: free and familiar, though most PMs at startups eventually outgrow it for feature-level adoption questions.

For product managers at startups, at what point did generic web analytics stop being enough for feature adoption tracking?

Digital Analytics reviews on G2 for product-focused tools describe event tracking as a design choice with real tradeoffs, not just a feature checkbox. Mixpanel's event and funnel structure mapping directly onto feature adoption questions requires deciding what to track upfront, while Heap's automatic capture of every interaction trades that upfront design work for a much larger, less curated dataset to sort through later. Kissmetrics' focus on cohort and behavior analysis over raw traffic reporting and Appier AIRIS's cross-touchpoint journey tracking both point at the same underlying shift the post describes, moving from counting visits to understanding a specific user's path through a product.

Google Analytics showing up here mainly as the tool startups eventually outgrow is a fair characterization, since it was built for marketing-style traffic reporting first, and retrofitting it to answer feature-level adoption questions tends to take real workaround effort compared to a tool built around events from the start. The post's own question about when generic analytics stopped being enough is probably answered by a specific moment rather than a gradual realization, usually when a PM needed to know whether a particular feature was actually being used and found the existing tool couldn't answer that without serious reconfiguration.

Answered: Shashank Shastry on September 17, 2026

Which Online Community Management tools reduce moderation burden while keeping engineering teams engaged daily?

Which online community management tools reduce moderation burden while keeping engineering teams engaged daily is a narrower ask than it looks, since most of what's written here focuses on community managers, not the engineers who'd actually be active daily participants. Checking online community management reviews for moderation and engagement specifics:

Gainsight Customer Communities: AI moderation and engagement features cut down significantly on manual post review, with ongoing platform updates continuing to expand automated group management functionality.
Circle: Replacing multiple disconnected tools with one organized platform reduces the administrative load of running engagement across different member segments and content types.
Hivebrite: AI features already handle member matching and networking suggestions, with more automation for tasks like page and event creation clearly on the roadmap based on what admins are asking for.
Mighty Networks: A 24/7 AI CoHost provides immediate setup and configuration help, reducing how much admin time goes into day-to-day platform management.

I genuinely don't have strong evidence either way on the engineering-specific daily engagement piece, that's a narrower slice than what most reviews cover. Has anyone actually gotten engineers to participate in a community platform as active daily users rather than occasional lurkers? What made that happen for you?

The moderation side is easier to validate than the engineering-engagement side. I’d look for platforms that automate spam, routing, and repetitive admin work while still giving engineers reasons to return, technical Q&A, product feedback loops, searchable discussions, and integrations with the tools they already use.

Answered: Darshayita Thakur on September 17, 2026