Marketing Software Resources - Page 34

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 personalization engines are rated highest for conversion uplift, based on user reviews?

Question for the reviewers and researchers here, with one honest caveat up front: every engine claims conversion uplift, and G2 ratings measure satisfaction, not lift, so "rated highest for uplift" really means whose reviewers keep crediting the tool with conversion gains in their own words. On that basis, the current G2 ratings picture in the Personalization Engines category:

Bloomreach (4.6, 735+ reviews): the largest review base of the pure personalization plays, with reviewers repeatedly connecting its recs to engagement and conversion outcomes.
Nosto (4.6, 235+ reviews): matches Bloomreach's rating with a smaller-merchant reviewer profile, where uplift claims are most concrete.
Dynamic Yield (4.5, 155+ reviews): reviewers describe revenue-driving personalization, with its 9.4 recommendations score the standout.
Optimizely Web Experimentation (4.2, 405+ reviews): the one whose method proves uplift rather than promising it, every gain arrives with a test behind it.
Adobe Target (4.0, 65+ reviews): the enterprise ecosystem play; its rating sits on a small review base relative to its footprint.

Also frequently queried alongside these: Kameleoon at 4.6 (135+ reviews).

On what basis would you actually credit a tool with uplift, its own dashboard, a holdout test, or something harder?

I’d only credit the tool after a holdout test. A personalization dashboard can tell you what happened after recommendations were shown, but not necessarily what would have happened without them. That’s where Optimizely’s experimentation angle gets interesting: proving incremental lift is a different job from reporting conversions.

Answered: Barkha Bali on August 21, 2026

What are the best ecommerce personalization engines for dynamic recommendations?

Hi, ecommerce folks on G2, this one's for you. I'm mapping the best personalization engines for e-commerce, specifically dynamic recommendations that respond to the shopper in front of them, and a shift is worth naming first: search vendors are now showing up in personalization shortlists, because "what to show this shopper" and "what this shopper searched" are converging into one relevance problem.

From the Personalization Engines category, the shortlist half-writes itself, Bloomreach, Dynamic Yield, Nosto, plus two crossing over from search:

Bloomreach (4.6, 735+ reviews): commerce-native recs on a real-time data layer; strongest where merchandising and marketing share one platform.
Dynamic Yield (4.5, 155+ reviews): reviewers rate its product recommendations 9.4, the highest signal in this set for the exact question asked.
Nosto (4.6, 235+ reviews): the ecommerce pure-play, quickest path from install to conversion-rate impact for smaller teams.
Algolia (4.5, 440+ reviews): a search platform by category, entering these shortlists as search results themselves become personalized surfaces.
Constructor (4.8, 55+ reviews): enterprise commerce search built on shopper-intent learning; small review base, striking scores.

What's missing here, and does anyone else see search and personalization collapsing into one buying decision?

I’d probably add Adobe Target to the conversation for larger teams. And yes, I do think search and personalization are starting to blur together, especially when the same behavioral data is driving both recommendations and ranked search results.

Answered: Preksha Buttan on August 26, 2026

Which personalization engines keep recommendations relevant with real-time content updates?

Curious how the personalization community reads this. Relevance is a moving target: a shopper's intent changes within a session, and stock changes under the catalog, so the real question is which engines keep recommendations relevant through real-time content updates.

Researching the Personalization Engines category, staying fresh comes down to three mechanisms worth checking in any demo: in-session behavioral signals (recs shift as the visitor clicks), live catalog sync (sold-out items drop out instantly), and real-time decisioning at page load rather than precomputed segments.

How the four names in this category approach it:

Dynamic Yield (4.5, 155+ reviews) is built around real-time decisioning across web, app, and email.
Bloomreach (4.6, 735+ reviews) pairs recs with a real-time customer data layer, so the profile updates mid-session.
Optimizely Web Experimentation (4.2, 405+ reviews) brings experimentation discipline, relevance validated by live tests.
Adobe Target (4.0, 65+ reviews) draws on Adobe's unified profile for real-time offer decisions, strongest inside that ecosystem.

For anyone who's run one of these against a fast-moving catalog: what actually kept recommendations current in practice, the algorithm, or the discipline of your product feed?

Oh for real-time relevance, the behavior-driven engines are what you want, not a static rules setup. Insider (rated very high on G2 at 4.8) is built around real-time, cross-channel personalization that updates as customer behavior changes, and Bloomreach is strong on real-time product discovery and recommendations. If you're ecommerce specifically, Nosto does real-time onsite personalization well. Optimizely is worth a look if you want experimentation baked into the personalization. Honest note, I'm going on their category positioning and ratings here rather than a deep per-review read, so I'd confirm exactly how "real-time" each one is (streaming vs batch updates) in a demo, since that varies a lot. What are you personalizing, a website, email, or app?

Answered: Hasitha Varre on November 3, 2026