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Case Studies on Data-Driven Marketing Strategies

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Should Marketing Strategies be data- driven or Instincts driven?
r/marketing • 1
Quick question for all the marketers
r/marketing • 2
Should Marketing Strategies be data- driven or Instincts driven?
r/MarketingHelp • 3
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Case Studies on Data-Driven Marketing Strategies

Finding Case Studies

To find case studies related to data-driven marketing strategies, several resources are recommended. Websites like HubSpot and Neil Patel offer a wealth of case studies and insights into successful marketing campaigns [2:1]. Additionally, Google Scholar can be a valuable resource for academic perspectives on marketing strategies [2:1]. For more industry-specific examples, ad agencies often have public repositories of their case studies, and award submissions or winners from events like Cannes Lions and Effie Awards can provide detailed analyses of successful campaigns [2:3].

Data-Driven vs. Instinct-Driven Strategies

The debate between data-driven and instinct-driven marketing strategies is ongoing. While data provides essential evidence and insights, instinct and creativity play crucial roles in designing effective marketing plans [1:2], [3:1]. A balanced approach that combines data with creative instincts can lead to more holistic and successful marketing strategies.

Utilizing Data in Marketing

In the realm of pay-per-click (PPC) advertising, a data-driven mindset is essential. Analyzing metrics such as Conversion Rate (CR), Click-Through Rate (CTR), and Cost Per Acquisition (CPA) helps identify issues and optimize campaigns for better performance [4]. This analytical approach allows marketers to make informed decisions and adjust strategies based on real-time data.

Strategic Planning and Execution

For marketers focusing on strategy, understanding the full customer lifecycle and aligning marketing efforts with broader business goals is crucial [5:6], [5:12]. This involves conducting internal research, engaging with sales and product teams, and ensuring feedback loops to measure the impact of strategies [5:1], [5:5]. Strategic planning also includes analyzing market trends, consumer behaviors, and competitors' programs to identify opportunities and develop effective campaigns [5:11].

Recommendations Beyond Discussions

Beyond the discussions, it's beneficial to look at industry reports and niche market analyses that are published annually. These can provide insights into emerging trends and successful strategies within specific sectors [2:5]. Engaging with professional networks and attending marketing conferences can also offer valuable case studies and firsthand accounts of successful data-driven marketing strategies.

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Source Threads

POST SUMMARY • [1]

Summarize

Should Marketing Strategies be data- driven or Instincts driven?

Posted by 4CNmims · in r/marketing · 3 years ago
4 upvotes on reddit
3 replies
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ORIGINAL POST

Imagine you have to choose a restaurant for your family dinner this weekend. After spending hours digging through multiple options, it boils down to the two – One that you prefer, the other which is a bestseller among the customers.

Now, you are the one going out to eat, so what matters the most is the one that suits you well. Meanwhile, the other restaurant has been voted bestseller for a reason and should be considered. If you find yourself troubled at the thought of making the choice, don’t worry, you are not alone. Businesses these days have been facing the same dilemma.

In the initial years of business operations, marketing was the product of the instincts and gut feelings of the people behind it. However, today marketers turn to the most reliable source of information: Customer data. Data-driven marketers use customer data to predict their needs and desires. Such insight helps develop personalised marketing strategies for the highest possible return on investment (ROI

Marketing departments in all companies have made strides in reducing the importance of ‘trusting your gut’ while making decisions. Today, we have more data than ever before to make informed decisions. The ability to analyse data, understand segmentation, and decipher the highest probability of success from user tests has been of key importance in the marketing industry. However, this will require brands to update their modelling—from pulling in the new lot of data to retraining algorithms.

Today’s customers are sceptical about the generic marketing messages they receive. One study revealed 74% of customers felt frustrated by receiving generic content from brands. Many of the respondents won’t consider an offer unless a brand personalises it to their previous interactions with them.

Personalisation of campaigns has led to targeting well-defined marketing segments, getting new customers and has also helped to improvise their marketing strategies over time.

With due importance to another school of thought, before the 20th century, marketers relied mostly on trial and error. The people who were the best at making these decisions by listening to their gut built the most successful businesses. Steve Jobs is one of the astute marketers of all time. Jobs bet on his understanding of what the general public needed: simplicity.

Don’t give customers more options; make things white and black. While the marketing industry today is new, the human brain is not. So, while data is more efficient than ever, a marketing team will never be complete without people who have a deep understanding of human psychology.

Considering and analysing both the strategies for developing marketing schemes shows that they both have their respective strong points and drawbacks. Data-driven marketing departments can concoct personalised advertisements based on customer data. However, the process of collecting, organising, and analysing so much data requires hefty capital investment. Instincts-driven marketing implies a deep understanding of human psychology and acting upon it. The problem arises that it may not always be coherent and is a subjective matter.

Bottom Line

An ideal marketing strategy can be the one that blends both taking the best out of the two and eliminating their shortcomings. To conduct the correct types of data experiments, having someone who understands customer needs is essential. A wise marketer makes their creative team and data geeks work in close coordination. One without the other will keep playing constant catch up, but the perfect mix of both will be the best recipe for massive growth.

- Saumya Pandey

3 replies
JovisSE · 3 years ago

Isn’t this already the case? Data helps you find relevant information about your campaign and external stake holders. Once you have that information you still need to take instinctive decisions when working with the campaign. Data can help you, but designing a plan takes more then just numbers.

2 upvotes on reddit
D
deletedtheoldaccount · 3 years ago

Thanks Jarvis I really needed this wall of text

1 upvotes on reddit
A
AutoModerator · 3 years ago

If this post doesn't follow the rules report it to the mods.

I am a bot, and this action was performed automatically. Please contact the moderators of this subreddit if you have any questions or concerns.

1 upvotes on reddit
See 3 replies
r/marketing • [2]

Summarize

Quick question for all the marketers

Posted by Successful_Scene3655 · in r/marketing · 5 months ago

Where can I find case studies related to marketing? brands and campaigns related.

4 upvotes on reddit
5 replies
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5 replies
Shamajo · 5 months ago

Use the deep research tool on ChatGPT. It will ask you what industry, what facet of marketing (guerrilla, outdoor, rebrand, digital, social) and marketing (USA, UK eyc) and give you some great outputs. When I use this tool, I also specify year is Only case studies post covid.

2 upvotes on reddit
BottleInBond · 5 months ago

Ad Agencies will practically always have a public repository of their case studies. Award submissions and winner (Cannes Lions, Effie, Clio, etc.) are also a great resource.

1 upvotes on reddit
drrevo74 · 5 months ago

Harvard Business review

1 upvotes on reddit
madhuforcontent · 5 months ago

Look for your niche industry reports that are generally published annually.

1 upvotes on reddit
No-Bookkeeper6050 · 5 months ago

You can check out sites like HubSpot, Neil Patel, or even Google Scholar for some solid case studies. 

5 upvotes on reddit
See 5 replies
r/MarketingHelp • [3]

Summarize

Should Marketing Strategies be data- driven or Instincts driven?

Posted by 4CNmims · in r/MarketingHelp · 3 years ago

Imagine you have to choose a restaurant for your family dinner this weekend. After spending hours digging through multiple options, it boils down to the two – One that you prefer, the other which is a bestseller among the customers.

Now, you are the one going out to eat, so what matters the most is the one that suits you well. Meanwhile, the other restaurant has been voted bestseller for a reason and should be considered. If you find yourself troubled at the thought of making the choice, don’t worry, you are not alone. Businesses these days have been facing the same dilemma.

In the initial years of business operations, marketing was the product of the instincts and gut feelings of the people behind it. However, today marketers turn to the most reliable source of information: Customer data. Data-driven marketers use customer data to predict their needs and desires. Such insight helps develop personalised marketing strategies for the highest possible return on investment (ROI

Marketing departments in all companies have made strides in reducing the importance of ‘trusting your gut’ while making decisions. Today, we have more data than ever before to make informed decisions. The ability to analyse data, understand segmentation, and decipher the highest probability of success from user tests has been of key importance in the marketing industry. However, this will require brands to update their modelling—from pulling in the new lot of data to retraining algorithms.

Today’s customers are sceptical about the generic marketing messages they receive. One study revealed 74% of customers felt frustrated by receiving generic content from brands. Many of the respondents won’t consider an offer unless a brand personalises it to their previous interactions with them.

Personalisation of campaigns has led to targeting well-defined marketing segments, getting new customers and has also helped to improvise their marketing strategies over time.

With due importance to another school of thought, before the 20th century, marketers relied mostly on trial and error. The people who were the best at making these decisions by listening to their gut built the most successful businesses. Steve Jobs is one of the astute marketers of all time. Jobs bet on his understanding of what the general public needed: simplicity.

Don’t give customers more options; make things white and black. While the marketing industry today is new, the human brain is not. So, while data is more efficient than ever, a marketing team will never be complete without people who have a deep understanding of human psychology.

Considering and analysing both the strategies for developing marketing schemes shows that they both have their respective strong points and drawbacks. Data-driven marketing departments can concoct personalised advertisements based on customer data. However, the process of collecting, organising, and analysing so much data requires hefty capital investment. Instincts-driven marketing implies a deep understanding of human psychology and acting upon it. The problem arises that it may not always be coherent and is a subjective matter.

Bottom Line

An ideal marketing strategy can be the one that blends both taking the best out of the two and eliminating their shortcomings. To conduct the correct types of data experiments, having someone who understands customer needs is essential. A wise marketer makes their creative team and data geeks work in close coordination. One without the other will keep playing constant catch up, but the perfect mix of both will be the best recipe for massive growth.

- Saumya Pandey

5 upvotes on reddit
1 replies
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View Source
1 replies
world-of-bertttt · 3 years ago

This is a great post, and I'll circle back to this once I've thoroughly read and digested it, but I think marketing should be both. Yes, I know lame answer!

At the end of the data provides some evidence. Your gut instincts, logic, and creativity paint a holistic picture (hopefully) - which data should also back up most of the time. However, you will never have data on everything - which is why our own thought processes and logic need to come into play.

1 upvotes on reddit
See 1 replies
r/PPC • [4]

Summarize

How Do You Utilize Data-Driven Strategies in Your Marketing

Posted by Huynhduchuy07 · in r/PPC · 2 years ago

Hi guys, do you apply a data-driven mindset in the PPC field? If you do, how do you apply it when analyzing data and finding the next steps?

From my perspective, I always use a data-driven approach to identify the root cause of problems when I'm not getting good results from running Facebook ad campaigns. For instance, if I run a conversion ad campaign for 7 days and the ROAS (Return on Ad Spend) is really low, I will download the campaign data and examine whether the Conversion Rate (CR) or Click-Through Rate (CTR) is the main issue, or if the Cost Per Click (CPC) is significantly high.

If the Conversion Rate is low, I will revisit the product page to see if there are any issues that might be affecting the conversion process. For CTR, I will examine the creatives used in the ads to determine if they are engaging and resonating with the target audience.

3 upvotes on reddit
1 replies
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1 replies
Vthead · 2 years ago

Google rep here (jk not really): have you tried increasing your budget.

4 upvotes on reddit
See 1 replies
r/marketing • [5]

Summarize

What do marketers who focus on strategy do all day?

Posted by theedrama · in r/marketing · 1 year ago

I’ve been moved into a role that focuses on campaign strategy for a specific segment. I’m used to actually building the programs too, but since I won’t be doing that anymore, I’m not sure what I’m supposed to be doing other than planning and pulling reports. And yes, I have asked for clarification from my boss but still feel like I won’t have a lot to do.

115 upvotes on reddit
12 replies
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12 replies
M
MagicalOak · 1 year ago

Hubspot has tons of resources on this subject matter... and much more.

13 upvotes on reddit
BasketNo4817 · 1 year ago

Good planning takes time and coordination with your stakeholders. Hardly a job to day dream about unless it doesnt click.

More research and thinking in broader terms of the business impact, not the campaign impact per se. Your new reports will need to report the why a budget is required as they learn the segment. Guide, listen and manage them so they are successful.

28 upvotes on reddit
T
theedrama · OP · 1 year ago

Thanks! I could do more research into the business impact. The issue is I work more on the B2B customer side so the campaigns I work on are not tied to revenue or leads, only retention but contracts are long.

8 upvotes on reddit
M
mickypaigejohnson · 1 year ago

Do internal research. Talk to sales, product and customer teams. Make sure there are feedback loops so you can measure the impact of the strategy. Find out what their challenges are and find ways to use marketing to proactively improve issues down the funnel.

For example, if account managers are having a churn problem, then improve targeting for marketing and coordinate with product/customer teams for better onboarding and expectation setting.

Well, this is in smaller to mid sized orgs. How big of an employee count does your org have?

5 upvotes on reddit
C
channeldrifter · 1 year ago

Research and develop stress-headaches, then throw it all out the window to create a PowerPoint deck to explain for the millionth time what marketing is and why it’s a) not sales b) not a fucking miracle and c) something that needs actual investment and buy-in and not just an afterthought budget to “make some stuff go viral on Instagram”, but mainly stress-headaches.

21 upvotes on reddit
T
theedrama · OP · 1 year ago

Thankfully I work for a company where leadership understands the importance of marketing

5 upvotes on reddit
W
wildcard_71 · 1 year ago

An important part of your role is to help executives understand the value of the marketing efforts. It's more than just getting the data. You will need to show how effort fits with results and make recommendations for future effort. You will also need to decide what are winning strategies and sell these ideas. Depending on the organization, you may also be called on to align, realign, align again, and align just for alignment sake.

10 upvotes on reddit
UniquerUser · 1 year ago

Look at market trends, consumer behaviors, and competitors' programs. Focus on channel planning. Understand yearly deadzones where sales are down, build out promos to leverage during those times. I'd say you'll never run out of things to do if you are doing it right.

224 upvotes on reddit
BeKindBeBrave · 1 year ago

This is a fantastic list. I'd also advise spending a fair amount of time understanding the business top to bottom, especially keying into broader business goals. And analysing the full sales funnel.

1 upvotes on reddit
LittleMsSpoonNation · 1 year ago

Agree with all the above however, don’t just stop at the sales funnel. I would want a full picture of the customer life cycle.

1 upvotes on reddit
A
alone_in_the_light · 1 year ago

My experience is more with marketing strategy instead of campaign strategy. There may be a lot to do before developing campaign strategies. For example, we may need to have strategies for the positioning of the company, a new target for the campaigns, or even to collect and manage data.

So, the work to me often starts very early in the process. If there are no campaigns and programs, part of the work is identifying opportunities to do something, we don't wait for things to happen. For example, check trends, analyze the competition, and talk to people inside and outside the company. Unless the company is already doing really well, there should be a lot of things we could do.

But things can be different at your company. I often make a distinction between people who are problem finders and problem solvers in marketing.

Problem solvers often need someone to bring the problem to them, in the form of a program or a campaign, for example. Then they solve the problem.

Problem finders keep looking and seeing if they can find problems, often before someone thinks of making a program or a campaign.

38 upvotes on reddit
T
theedrama · OP · 1 year ago

Really good points/ideas. There are other projects I’ve been assigned such as mapping out processes. I think I could dive deeper into trends

8 upvotes on reddit
See 12 replies
r/promptingmagic • [6]

Summarize

The Ultimate ChatGPT Marketing Playbook: 40 Awesome Digital Marketing Prompts That Actually Convert - SEO, Content Marketing, PPC, Analytics, Marketing Automation and Campaigns

Posted by Beginning-Willow-801 · in r/promptingmagic · 10 days ago
post image

TLDR Summary:

40 hyper-optimized ChatGPT prompts that cover every aspect of digital marketing - from content strategy to conversion optimization. Each prompt includes specific variables, context parameters, and output formats that deliver agency-level results.

The Ultimate ChatGPT Marketing Playbook: 40 Battle-Tested Prompts That Actually Convert

Listen up, marketers.

These aren't your generic "write me a blog post" prompts. These are precision-engineered, variable-rich frameworks that output marketing gold every single time. These can be used on ChatGPT, Claude or Gemini. The key to getting great results for these is to attach the right inputs, attachments and context about your company, products, and campaigns to the prompts below. The more specific you are the better results you will get.

It makes sense to test these prompts across the three major LLMs and compare outputs
Gemini has the largest context window for large outputs
Claude can generate spreadsheets and presentations
ChatGPT and Claude give some of the best writing

Why these prompts hit different:

  • Each includes specific context parameters for maximum relevance
  • Built-in quality checks and optimization layers
  • Structured outputs that plug directly into your workflow
  • Tested across B2B, B2C, SaaS, and e-commerce

Let's dive in.

🎯 CONTENT MARKETING STRATEGY (5 Prompts)

1. Content Calendar Architect

"You are a strategic content planner. Create a 90-day content calendar for [company] in the [industry] space. Target audience: [demographics, psychographics, pain points]. Business goals: [specific metrics]. Include: content pillars (4-6 themes), posting frequency per channel, content formats mix (60% educational, 25% promotional, 15% engagement), topic clusters with semantic SEO keywords, repurposing matrix showing how each piece transforms across platforms, and performance KPIs for each content type. Format as a table with columns: Date, Topic, Format, Channel, Keywords, CTA, Success Metric."

2. Topic Authority Builder

"Analyze the [niche] market and identify 20 underserved topic opportunities where [company] can establish thought leadership. For each topic provide: search volume data estimates, competition level (1-10), content gap analysis, unique angle we can own, supporting subtopics (minimum 5), expert sources to reference, and potential partnership/collaboration opportunities. Prioritize by impact/effort ratio and create a 6-month authority building roadmap."

3. Pillar Content Blueprint

"Design a comprehensive 10,000-word pillar page for [topic] targeting [audience]. Structure: compelling hook (3 variations), executive summary with key takeaways, 15-20 H2 sections with detailed subsections, original data points or industry insights, 10 actionable templates/frameworks readers can implement, internal linking strategy (minimum 20 contextual links), FAQ section addressing top 15 questions, and 5 content upgrades for lead generation. Include meta description, title variations for A/B testing, and social media promotional snippets."

4. Content Repurposing Engine

"Take this [content piece/URL] and create a repurposing strategy that generates 20 unique assets. Break down into: 5 short-form social posts with native formatting, 3 email newsletter sections, 2 video script outlines (60-second and 5-minute versions), 1 podcast talking points document, 1 infographic data story, 5 LinkedIn carousel slides, 10 Twitter/X thread components, 3 YouTube Shorts hooks, and 1 comprehensive slide deck. Maintain core message while optimizing each for platform-specific engagement patterns."

5. Engagement Optimizer

"Audit this content: [paste content or URL]. Provide enhancement recommendations across 10 dimensions: headline power score (1-100) with 5 alternatives, opening hook effectiveness with rewrites, storytelling elements to add, data/statistics to include, visual content suggestions, interactive elements, readability score optimization, emotional triggers analysis, CTA placement and copy variants, and SEO optimization opportunities. Output specific before/after examples for each dimension."

📱 SOCIAL MEDIA MARKETING (5 Prompts)

6. Viral Content Formula

"Create 10 social media posts for [platform] about [topic] optimized for maximum organic reach. Each post must include: attention-grabbing hook (first 7 words), story arc or value proposition, specific data point or surprising fact, emotional trigger (curiosity/fear/desire/belonging), clear visual description or actual visual prompt, engagement mechanism (question/poll/challenge), strategic hashtag mix (3 niche, 3 medium, 2 broad), optimal posting time based on audience, and 3 comment response templates to boost engagement. Format for easy copy/paste with character counts."

7. Community Growth Hacker

"Develop a 30-day community building campaign for [brand] on [platform]. Include: daily engagement tasks (comment, share, create), influencer outreach templates (5 variations), UGC campaign framework with incentive structure, community guidelines and moderation playbook, crisis management protocols, ambassador program structure, engagement pods strategy (ethical approach), content themes that spark discussion, live event/AMA calendar, and metrics dashboard tracking community health indicators. Provide week-by-week implementation timeline."

8. Platform-Specific Optimizer

"Optimize our [platform] presence for [goal: awareness/engagement/conversion]. Analyze current performance gaps and provide: profile optimization checklist (bio, links, keywords), content mix ratio for algorithm favorability, posting schedule based on audience activity, hashtag research with 50 categorized options, competitor analysis of top 5 accounts, content templates for 10 post types, engagement tactics specific to platform culture, paid promotion strategy with budget allocation, influencer collaboration opportunities, and monthly performance benchmarks to hit."

9. Social Commerce Converter

"Design a social selling funnel for [product/service] on [platform]. Map out: awareness stage content (5 concepts), consideration stage content (5 concepts), decision stage content with social proof, shoppable post templates with psychological triggers, limited-time offer frameworks, customer testimonial formats, influencer partnership structure for sales, retargeting content for cart abandoners, post-purchase advocacy content, and ROI tracking methodology. Include actual copy examples and visual directions."

10. Trend Hijacker Pro

"Monitor and capitalize on trending topics for [brand] in [industry]. Create: trend identification framework, relevance scoring matrix (brand fit 1-10), rapid response content templates (5 formats), trend-jacking guidelines and boundaries, real-time marketing calendar, meme adaptation templates, viral moment preparation kit, legal/PR consideration checklist, performance prediction model, and post-trend analysis framework. Provide 5 current trend opportunities with execution plans."

🔍 SEO & WEB TRAFFIC (5 Prompts)

11. Keyword Domination Strategy

"Conduct deep keyword research for [website/niche]. Identify: 50 primary keywords with search volume and difficulty scores, 200 long-tail variations with buyer intent indicators, 30 question-based keywords for featured snippets, 20 'People Also Ask' opportunities, 15 voice search optimized phrases, competitor keyword gaps (analyze top 5 competitors), seasonal keyword opportunities with timing, local SEO keywords if applicable, semantic keyword clusters for topical authority, and negative keywords to avoid. Create 6-month ranking roadmap with content priorities."

12. Technical SEO Audit Commander

"Perform comprehensive technical SEO audit for [website]. Check: site speed optimization opportunities (Core Web Vitals), mobile responsiveness issues, crawlability and indexation problems, XML sitemap optimization, robots.txt configuration, schema markup implementation gaps, internal linking structure analysis, broken links and redirect chains, duplicate content issues, canonical tag problems, image optimization needs, SSL and security factors, and international SEO considerations. Provide prioritized fix list with implementation guides."

13. Link Building Machine

"Create link building campaign for [website] in [industry]. Develop: 30 high-authority target sites with outreach templates, 10 linkable asset ideas with production briefs, HARO response templates for 5 categories, guest posting opportunities with pitch templates, broken link building prospects, resource page targets, partnership and collaboration angles, digital PR story angles, infographic distribution strategy, and competitor backlink replication opportunities. Include outreach email sequences and follow-up schedules."

14. Content Gap Assassin

"Analyze content gaps for [website] versus top 3 competitors. Identify: missing topic clusters, underserved search queries, thin content improvement opportunities, FAQ and Q&A gaps, video content opportunities, tool and calculator ideas, template and resource gaps, case study angles not covered, geographic content gaps, and user intent mismatches. Create content production calendar addressing top 20 gaps with keyword targets and success metrics."

15. Featured Snippet Hunter

"Optimize [website/content] for featured snippet domination. Target: paragraph snippets (20 opportunities), list snippets (15 opportunities), table snippets (10 opportunities), video snippets strategy, 'People Also Ask' box optimization, knowledge panel optimization, FAQ schema implementation, How-to schema opportunities, definition box targeting, and comparison snippet formats. Provide exact content formatting, word counts, and HTML structure for each snippet type."

✉️ EMAIL MARKETING (5 Prompts)

16. Welcome Series Architect

"Design a 7-email welcome series for [brand] targeting [customer segment]. Email 1: Brand story and value proposition with 3 subject line variants. Email 2: Social proof and success stories with segmentation triggers. Email 3: Educational content establishing expertise with content upgrades. Email 4: Product/service deep dive with interactive elements. Email 5: Exclusive offer with urgency mechanisms. Email 6: User-generated content and community invitation. Email 7: Feedback request and preference center. Include A/B test variables, timing sequences, and performance benchmarks for each email."

17. Re-engagement Resurrection

"Create win-back campaign for dormant email subscribers of [company]. Develop: segmentation strategy for inactive periods (30/60/90/180 days), re-engagement email series (4 emails per segment), subject lines optimized for opens (10 variants to test), personalization variables beyond just name, incentive escalation strategy, content preference survey, sunset policy for non-responders, list hygiene protocols, and success metrics for campaign evaluation. Include emotional triggers and value reminders specific to each inactivity period."

18. Segmentation Scientist

"Build advanced email segmentation strategy for [business] with [list size] subscribers. Create: demographic segments with personas, behavioral segments based on engagement patterns, purchase history segments with RFM analysis, content preference segments, lifecycle stage segments, geographic and timezone segments, device and email client segments, lead scoring model, dynamic content rules for each segment, and automated workflow triggers. Provide campaign ideas tailored to each segment with expected performance metrics."

19. Newsletter Money Machine

"Transform [company] newsletter into revenue driver. Design: content structure balancing value and promotion (70/20/10 rule), monetization opportunities without sacrificing trust, sponsored content integration guidelines, affiliate marketing implementation, product placement strategies, exclusive offer frameworks, cross-sell and upsell sequences, advertiser media kit template, subscriber growth tactics, and retention optimization strategies. Include 12-month revenue projection model with growth scenarios."

20. A/B Testing Laboratory

"Create comprehensive A/B testing framework for [company] email program. Test: subject line formulas (15 variants), preview text optimization, sender name variations, send time experiments, design layouts (3 templates), CTA button variations (copy, color, placement), personalization depth levels, image vs. text ratios, email length optimization, and urgency/scarcity tactics. Provide testing calendar, sample size calculator, statistical significance thresholds, and results documentation template."

💰 PPC ADVERTISING (5 Prompts)

21. Google Ads Dominator

"Build Google Ads campaign for [product/service] with [budget]. Create: campaign structure with ad groups, 50 keyword variations with match types, 20 negative keywords to exclude, 10 responsive search ads with multiple headlines/descriptions, 5 ad extensions (sitelink, callout, structured snippet, call, location), audience targeting parameters, bidding strategy recommendations, landing page optimization checklist, quality score improvement tactics, and day-parting schedule. Include competitive analysis and budget allocation across campaigns."

22. Facebook Ads Alchemist

"Design Facebook/Meta ads funnel for [business] targeting [audience]. Develop: campaign objectives for each funnel stage, detailed audience personas with targeting parameters, creative briefs for 10 ad variations (image, video, carousel), copy frameworks emphasizing different psychological triggers, custom audience strategies (lookalike, retargeting, exclusions), placement optimization across Meta properties, budget distribution using campaign budget optimization, pixel event tracking setup, iOS 14.5+ workarounds, and performance benchmarks by industry."

23. LinkedIn Ads B2B Sniper

"Create LinkedIn advertising strategy for [B2B company] targeting [job titles/industries]. Build: account-based marketing campaign structure, matched audiences using company lists, job title and seniority targeting matrix, content formats for each funnel stage (sponsored content, message ads, video), thought leadership ad templates, lead generation form optimization, conversation ad sequences, retargeting strategies for different engagement levels, integration with CRM for lead scoring, and ROI calculation model including pipeline attribution."

24. Shopping Ads Optimizer

"Optimize shopping campaigns for [e-commerce store] with [product catalog size]. Structure: campaign architecture by product category/margin, feed optimization checklist (titles, descriptions, images), bidding strategies for different product types, negative keyword sculpting, custom label strategies for segmentation, promotion extensions setup, competitive pricing intelligence, seasonal adjustment calendar, cross-selling campaign structure, and performance max campaign integration. Include automation rules and scripts for optimization."

25. Retargeting Revenue Machine

"Build retargeting ecosystem for [website] across all platforms. Create: audience segments based on behavior (viewers, cart abandoners, purchasers), dynamic product ads setup, sequential messaging strategy, cross-platform retargeting (Google, Facebook, LinkedIn), email retargeting integration, frequency capping rules, creative refresh schedule, offer escalation timeline, exclusion audiences to prevent fatigue, and attribution model for measuring impact. Provide platform-specific setup guides and budget recommendations."

📊 ANALYTICS & REPORTING (5 Prompts)

26. KPI Dashboard Architect

"Design comprehensive marketing dashboard for [company] tracking [goals]. Include: North Star metric definition, leading and lagging indicators, channel-specific metrics (organic, paid, social, email), conversion funnel visualization, cohort analysis setup, attribution modeling recommendations, custom dimensions and metrics, automated alerting thresholds, competitive benchmarking metrics, and ROI/ROAS calculations. Provide Google Analytics 4 setup guide, Data Studio template, and Excel/Sheets backup dashboard."

27. Attribution Decoder

"Solve attribution challenges for [business] with [customer journey complexity]. Develop: multi-touch attribution model comparison, channel interaction analysis, conversion path mapping, assisted conversion evaluation, time lag analysis, device cross-tracking setup, offline conversion tracking, view-through attribution for display/video, incrementality testing framework, and marketing mix modeling basics. Create attribution reporting template with channel contribution calculations."

28. Conversion Forensics Expert

"Analyze conversion rate for [website/funnel] and identify optimization opportunities. Examine: funnel visualization with drop-off points, user behavior flow analysis, device and browser performance, page speed impact on conversions, form analytics and abandonment, checkout process friction points, pricing page optimization, trust signal effectiveness, mobile experience gaps, and A/B test prioritization matrix. Provide 30-day CRO roadmap with expected lift calculations."

29. Competitor Intelligence System

"Build competitor monitoring framework for [company] tracking [top 5 competitors]. Monitor: traffic and ranking changes, content publishing frequency and topics, social media engagement rates, ad creative and copy changes, email marketing frequency and offers, new product or feature launches, pricing changes and promotions, partnership announcements, technology stack changes, and customer sentiment shifts. Create automated reporting system with alert triggers."

30. ROI Proof Generator

"Create marketing ROI reporting for [stakeholder type] showing [time period] performance. Include: executive summary with key wins, channel-by-channel ROI breakdown, customer acquisition cost trends, lifetime value calculations, marketing-influenced pipeline, brand lift measurement proxies, cost per acquisition by segment, marketing efficiency ratio, contribution margin analysis, and future performance projections. Design visual storytelling flow with data narratives that connect marketing to business outcomes."

🤖 MARKETING AUTOMATION (5 Prompts)

31. Lead Nurture Architect

"Design multi-touch lead nurturing system for [business] with [sales cycle length]. Create: lead scoring model with behavioral and demographic factors, progressive profiling strategy, content mapping to buyer journey stages, automated workflow triggers and branches, sales handoff criteria and SLA, re-engagement loops for stalled leads, lead recycling protocols, personalization token strategy, multi-channel orchestration (email, SMS, ads), and performance optimization framework. Include Marketo/HubSpot/Pardot implementation guide."

32. Behavioral Trigger Matrix

"Build behavioral automation for [platform/tool] based on user actions. Map: website behavior triggers (page visits, time on site, scroll depth), email engagement triggers (opens, clicks, forwards), purchase behavior triggers (cart, browse, buy), content consumption triggers (downloads, video views), social engagement triggers, milestone and date-based triggers, lead score threshold triggers, integration triggers from other tools, abandoned action recovery sequences, and trigger conflict resolution rules. Provide workflow diagrams and timing recommendations."

33. Chatbot Conversation Architect

"Create intelligent chatbot flows for [website/platform] serving [use cases]. Design: welcome message variations by traffic source, qualification question trees, intent recognition patterns, FAQ handling with 20 common questions, lead capture mechanisms, appointment booking flows, product recommendation logic, support ticket creation, human handoff triggers, and conversation recovery for abandoned chats. Include personality guidelines, error handling, and performance metrics to track."

34. Lifecycle Marketing Machine

"Develop lifecycle marketing automation for [SaaS/subscription business]. Build: onboarding sequence for new users (14-day flow), activation triggers and milestones, feature adoption campaigns, usage-based messaging triggers, upgrade and expansion campaigns, renewal and retention sequences, win-back campaigns for churned users, advocacy and referral programs, NPS/feedback automation, and customer health score automation. Map all touchpoints with message frequency governance."

35. Dynamic Content Engine

"Implement dynamic content strategy for [company] across all channels. Create: personalization variables inventory, content variation matrix by segment, dynamic email template system, website personalization rules, ad creative versioning system, landing page variation logic, product recommendation algorithms, geo-targeted content rules, time-based content scheduling, and testing framework for personalization impact. Include privacy compliance and fallback content strategies."

🎯 CONVERSION RATE OPTIMIZATION (5 Prompts)

36. Landing Page Optimizer

"Optimize landing page for [offer/product] targeting [audience]. Analyze: headline testing matrix (10 variants), value proposition clarity and hierarchy, social proof placement and types, form field optimization, CTA button psychology (copy, color, size, placement), page speed optimization checklist, mobile responsiveness audit, trust signals and security badges, urgency and scarcity implementation, and exit-intent strategies. Provide A/B test roadmap with statistical significance calculator."

37. Checkout Flow Surgeon

"Redesign checkout process for [e-commerce site] to minimize abandonment. Optimize: checkout steps and progress indicators, form field reduction strategies, guest checkout implementation, payment option optimization, shipping calculator placement, security and trust messaging, error handling and validation, save cart functionality, cross-sell/upsell opportunities, and post-purchase experience. Include abandonment recovery email sequences and remarketing strategies."

38. Pricing Page Psychologist

"Design high-converting pricing page for [product/service]. Structure: pricing table layout with visual hierarchy, feature comparison matrix, psychological pricing strategies, anchor pricing implementation, social proof integration, FAQ section addressing objections, money-back guarantee messaging, urgency triggers for decision-making, calculator or ROI tools, and plan recommendation algorithm. Provide copy templates emphasizing value over cost."

39. Social Proof Amplifier

"Maximize social proof impact for [website/product]. Implement: testimonial collection system, case study templates, review aggregation strategy, influencer endorsement display, media mentions and logos, user-generated content integration, real-time activity notifications, trust badges and certifications, customer success metrics, and community size indicators. Create placement strategy for maximum conversion impact with A/B testing framework."

40. Mobile Conversion Maximizer

"Optimize mobile experience for [website/app] conversions. Address: thumb-friendly navigation design, mobile-first form optimization, click-to-call implementation, mobile payment options, app download prompts, AMP or PWA implementation, mobile-specific offers, location-based features, offline functionality, and cross-device journey continuity. Include mobile-specific A/B tests and analytics setup for mobile behavior tracking."

PRO TIPS FOR MAXIMUM IMPACT

  1. Variable Customization: Replace all bracketed variables with your specific details. The more specific, the better the output.
  2. Chain Prompting: Use outputs from one prompt as inputs for another. Example: Use keyword research output for content creation.
  3. Version Control: Save successful outputs and create prompt templates for recurring tasks.
  4. Testing Protocol: Always generate 3-5 variations and test performance before scaling.
  5. Human Touch: These prompts generate foundations. Add your brand voice, industry expertise, and creative flair.

Marketing isn't about working harder. It's about building systems that compound.

These prompts aren't just time-savers. They're force multipliers.

Your competition is already using AI. The question is: are you using it better?

Start with 5 prompts. Master them. Then add 5 more.

You don't have to cut and paste all these prompts - you can add them to your personal prompt library on Prompt Magic with just one click for free. Get great prompts like the ones is this post at PromptMagic.dev

You can easily create your own personal prompt library, customize prompts and organize all your prompts into folders (collections) on Prompt Magic 

reddit.com
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Beginning-Willow-801 · OP · 10 days ago

https://preview.redd.it/gqlowkt5ueqf1.png?width=1024&format=png&auto=webp&s=e751339160d80b5c2c9d30e63deb5f0c1ece9998

1 upvotes on reddit
Beginning-Willow-801 · OP · 10 days ago

https://preview.redd.it/qpac0lb8ueqf1.png?width=1326&format=png&auto=webp&s=4218037bd34fa56fbda12601a8d5aa228798353f

1 upvotes on reddit
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South-Opening-9720 · 8 days ago

This is an absolute goldmine! 🔥 I've been struggling with creating consistent, high-quality prompts that actually deliver results rather than generic fluff.

The behavioral trigger matrix (#32) particularly caught my attention - I've been working on automating customer interactions and realized how crucial it is to map out every possible user action and response. Recently implemented something similar when building chatbot flows, and the difference in engagement was night and day.

What I love about these prompts is the specificity. Too many "AI marketing guides" give you basic templates, but these include actual variables, context parameters, and measurable outputs. The conversion forensics expert prompt (#28) is going straight into my optimization toolkit.

One thing I'd add - when implementing these automation workflows, having a solid chatbot foundation makes a huge difference. I've found Chat Data particularly useful for this since it integrates seamlessly with existing marketing stacks and provides the real-time analytics needed to optimize these automated sequences. The ability to escalate to human agents when the automation hits its limits has been a game-changer.

Thanks for putting this together - definitely bookmarking this for my team. The chain prompting tip is brilliant too!

2 upvotes on reddit
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r/PPC • [7]

Summarize

Anyone try Data Driven Attribution and go back to a previous model?

Posted by ilufppc · in r/PPC · 6 years ago

I get data driven but as an advertisers spending up to $150k/month I'm not seeing the types of conversion paths that would merit the benefits of data driven - starting w/ 1 campaign and converting in another.

I may go back to last click as of Oct 1.

Any thoughts from you PPC'ers?

12 upvotes on reddit
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zahcy · 6 years ago

Data Driven > Last Click

5 upvotes on reddit
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cuteman · 6 years ago

I don't think any one attribution model is right anymore than any one bidding strategy is correct. They are testing models that vary by advertiser, by budget, by funnel.

It's best to test these sorts of things while concurrently running to suss out potential positives and negatives.

It can lead to a paradigm shift but ultimately it's about looking at things from a new angle but you might get completely different results depending on how you run the campaign.

1 upvotes on reddit
RudeGoat · 6 years ago

Big fan of position based attribution personally

6 upvotes on reddit
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TTFV · 6 years ago

Yes, we use this for virtually any client that has some top of funnel activities or are using some broader keywords to drive interest and consideration.

Otherwise, we use time decay.

2 upvotes on reddit
octavianrc · 6 years ago

I have never seen a real reason to prefer last click over data driven models, other than making it easier to explain to old-school clients.
In case of very short journeys they may have similar results, but anything else is useful information.

Also, you may want to check more granular results, e.g. on keywords or product groups, depending on the granularity of your campaigns

1 upvotes on reddit
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ilufppc · OP · 6 years ago

Good thought, tho how is it possible to compare attribution models more granularly, say at the keyword or prod grp level?

1 upvotes on reddit
octavianrc · 6 years ago

I think google ads does it at keyword level, data-driven attribution on product groups etc. I have only seen in paid products, even GA360 doesn't show it (or I just couldn't make it work)

1 upvotes on reddit
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bkh_leung · 6 years ago

We've switched from last click to position based several months ago and it's helped us make smarter decisions on keywords that are higher up the funnel.

Data driven or position based are great when you pair that with smart bidding.

You should do an experiment on the bidding strategy vs attribution model.

6 upvotes on reddit
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r/Market76 • [8]

Summarize

Big Data and Its Big Impact on Marketing Strategy

Posted by AllThatClicks · in r/Market76 · 6 years ago
allthatclicks.com
1 upvotes on reddit
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AutoModerator · 6 years ago

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r/dataanalysis • [9]

Summarize

I'm a digital marketeer and was offered the position as a marketing data analyst - should I take it? anyone else in this field?

Posted by mas707 · in r/dataanalysis · 4 years ago

I'm asking as I'm quite concerned what my CV might look like afterwards.

I'm confident in working with Google Analytics and Google Data Studio, I know how to set up social media campaigns and I've studied a lot of marketing theory, I'm also experienced in developing specific strategies and funnels - but am I ready for focusing on data analysis? and what skills will it actually take?

My new position will require to report and analyze our campaigns performance and look for potential optimizations based on which we will create new campaigns. I ll be responsible for delivering the input. I ll also be responsible for ensuring the quality of data (e.g. by tracking, AB-Testings) and identifying new chances.

The reason I'm hesitating is: the things I mentioned above.. aren't these actually tasks of a performance marketeer or digital marketeer? or isn't this at least what's being expected of you to deliver if you're doing your job right?

I'm wondering if they're trying to sell the stuff others don't like to do (reportings) or don't have the time to do (reportings) as a 'great chance'. Tbh, in the past I did all by myself. I developed and executed campaigns, I've reported them and I delivered strategies based on data. I'm just wondering why anyone else wouldn't follow these steps through and hire someone just to do the unpleasant, dry tasks? my boss told me she needed someone that has a data mindset combined with marketing knowledge, which doesn't seem to be that common. I can't believe this is true as like I said before: it's something I would absolutely expect of a digital marketeer being capable of.. or are my expectations too high

8 upvotes on reddit
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[deleted] · 4 years ago

I made a similar jump a few years ago. You would think that all marketers would want to understand data and make data driven decisions! But math/data is hard for ... a lot of people.

If you like data + marketing, this could be a lucrative career path.

9 upvotes on reddit
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ViciousSquid · 4 years ago

Similar to u/SpinTheEgg, I recently made a transition from digital marketing specialist to digital analyst. It's not something I envisioned for myself, but my (now) boss saw potential in me. It was also a retention tactic to save me from our struggling DM department.

Reporting, tracking, and objective analysis are extremely important, but often overlooked. It's sometimes not prioritized; it's backburner stuff until something breaks or the client asks for more. But, you can gain a lot of authority, trust, and value with clients when you improve these areas and show them true ROI.

This could be a good opportunity if A) you're interested in any parts of this field B) if you have solid guidance and instruction.

I'd be totally stranded if it wasn't for my boss and teammate. Analytics work can go deep and technical. If they're putting you out on your own with no resources, then yes, they might just be looking for a report jockey, which isn't fair nor will it likely progress your career.

Like you, I'm not sure where this will lead me or how it'll affect my resume moving forward, but it's all about how you craft your experiences and narrative. Even if data isn't where you always want to be, it's certainly a great technical skill set to dip into and utilize elsewhere. I've learned a lot.

To answer your questions about skills, currently I'm touching things like: -Google Tag Manager -Google Analytics -Tableau -Data Studio -Data warehousing (may lead to things like SQL or Python) -Data privacy compliance -Digital marketing reporting -Website performance reporting

2 upvotes on reddit
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ViciousSquid · 4 years ago

Also, if you take the position, make sure it comes with a raise.

2 upvotes on reddit
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mas707 · OP · 4 years ago

oh, definitely! I was hired as a digital marketeer but will do the job of an analyst? there's a minimum gap of 600 bucks between those positions.. thank you also for your insights. :-)

2 upvotes on reddit
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redman334 · 4 years ago

Well.... It depends on what you want to do. If you want to be doing the reporting, and analyisis of campaigns, creating dashboards, watching over key metrics. Then yeah, go for it. But if you consider this the dry part, and rather like planing the campaign, looking at the designs, setting it up and so on, then don't. Honestly, I'm in the same position, I have a bachelor in marketing, and worked as half marketing half data analyst, and I liked much more the data analyst side rather than the marketing one. That's why I'm focusing on data analysis. If you want to head to data analysis, take into consideration that getting to know how to write on SQL, is quite important. It's all comnfi and good when all the data comes from google analytics directly into Data Studio, but I'm sure that half of the data you could get overall to analyse. In my case, I would go for it, and I did, but it's really up to you. I rather look at data and understand what is the course of action to take, and telling so, than being the one who has to do all the marketing things to set it on its way. Although both have it's pros and cons.

4 upvotes on reddit
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mas707 · OP · 4 years ago

thank you so much. I guess then we re kind of the same. I loved campaigning when I was still learning and working as a junior but now I'm also rather into data. When I was younger I never really loved mathematics, now I actually like to do it, also statistics. I recently also started learning some SQL. I'm just still wondering what's the job title after all, or what this skillset will be named on the job market?

1 upvotes on reddit
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redman334 · 4 years ago

Business intelligence analyst, data analyst, business analyst (this one sometimes, sometimes it's another thing).

2 upvotes on reddit
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dontich · 4 years ago

I have had both do it all roles and data analyst roles in digital marketing.

As teams get bigger you want to specialize, IE one people does reporting and pipelines, one person does FB, another Google another SEO etc.

As someone with a generalists background I'd say analyst is definitely a good starting spot on a larger team.

2 upvotes on reddit
SpinTheEgg · 4 years ago

I made a similar jump exactly a year ago. I had been in digital marketing for 11 years and felt like it was time to try something new. My role now is exactly what you described - data extraction, analysis and reporting.

I knew after 3 months that it wasn’t for me but the pandemic hit and I stuck it out. There were a few things I didn’t consider before making the jump. It was a totally new industry I’d never worked in and they used Adobe. I had previously worked in GA and data studio.

It does feels like I do the work our marketers don’t want to do. I plan to make the jump back to marketing but I do think there’s value in what I learned from the other data analysts and engineers I’ve partnered with this year. It also helped me focus on what I want to do with the rest of my career.

Also, I agree those capabilities are something I always thought marketers should handle but this year showed me many digital marketers are hesitant to take on.

3 upvotes on reddit
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mas707 · OP · 4 years ago

that's kind of what I'm concerned with. before I started in my recent job my CV rather marked me as an "allrounder" but I guess it's the specialist the market is looking for, and continuing with data analysis seems like another step to being an allrounder. what field would you jump back to?

1 upvotes on reddit
SpinTheEgg · 4 years ago

I’m a generalist as well. I’ve had every title - SEM Manager, SEO Manager, SEO/SEM Analytics Manager, Digital Marketing Manager, Paid Media Manager, Demand Generation Manager and Business Analytics Manager. I see them all as related in one way or another and contributing uniquely to my overall knowledge.

I have worried at times about not picking a specialty or not picking a lane but I wanted my own perspectives and opinions. I know now I want to get to the director-level. I would likely be there already if I didn’t jump around but I’ve also had directors that never gave direction because they never worked in a channel.

I’ll likely take another performance marketing or paid media manager position and work my way up the ranks. It’s never about the job titles you’ve had. It’s about the work experiences you can bring. I got my current job where I work with actual degree carrying data scientists and engineers because I had experience with marketing analytics and tagging.

3 upvotes on reddit
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r/marketing • [10]

Summarize

What are some of your favorite marketing case studies?

Posted by dorksly · in r/marketing · 4 years ago
54 upvotes on reddit
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partypat_bear · 4 years ago

American Airlines selling unlimited lifetime flight passes back in the 80s

27 upvotes on reddit
WeissIchWeiss · 4 years ago

Amazon. How in the world did any company manage to corner ecommerce? For any given purchase you can literally and easily search all available offers (via a search engine)... but somehow one company has become the first place people go to buy things online. To top it off, they did it with almost no advertising. They ignored a whole "P" of marketing and still dominate and un-dominatable market!

17 upvotes on reddit
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Thelonelywindow · 4 years ago

They were early on that.

3 upvotes on reddit
WeissIchWeiss · 4 years ago

Na, it was way more than that. It was an exercise of offering more than customers expected over and over again. 1 click shopping, reviews and customer Q&A, 2 day shipping, 1 day shipping, etc. They weren't the first. They were the best and kept getting better and better. And they played the long game. It was over a decade before they generated an profit.

2 upvotes on reddit
Jayko_Aldent · 4 years ago

Kodak is the one that get me. It's not just a story of a market leader being overconfident of its strengths or oblivious to change. They're the one who manage to invent digital image capture technology in the first place. Yet they decided not to exploit it in fear of cutting their margins on the traditional cameras.

You should not fear to innovate because of your current revenue. If you don't let your R&D department shake your short-term margins a bit, eventually your competitors will catch up and bring you to the ground.

50 upvotes on reddit
GroupShoddy1852 · 2 years ago

What does R&D mean ?

1 upvotes on reddit
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Orange-V-Apple · 1 year ago

Research and Development

1 upvotes on reddit
[deleted] · 4 years ago

Came here to say this.

3 upvotes on reddit
thepropropro · 4 years ago

��

2 upvotes on reddit
Jojodancer2525 · 4 years ago

��

1 upvotes on reddit
theaxelalex · 4 years ago

Let me think back to my overpriced education... coke vs. pepsi?

14 upvotes on reddit
dorksly · OP · 4 years ago

Domestication is the ultimate rebrand

1 upvotes on reddit
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Related

How to use data analytics to improve marketing performance

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AI Answer

🤖

case studies on data-driven marketing strategies

Key Considerations for Data-Driven Marketing Strategies:

  1. Definition and Importance: Data-driven marketing involves using data analytics to inform marketing decisions. It helps in understanding customer behavior, preferences, and trends, leading to more effective campaigns.

  2. Types of Data: Consider both qualitative (customer feedback, surveys) and quantitative data (sales figures, web analytics) to get a comprehensive view of your audience.

  3. Tools and Technologies: Familiarize yourself with tools like Google Analytics, CRM systems, and marketing automation platforms that can help collect and analyze data.

  4. Segmentation and Targeting: Use data to segment your audience based on demographics, behavior, and preferences. This allows for more personalized and relevant marketing efforts.

  5. Measurement and KPIs: Establish clear KPIs (Key Performance Indicators) to measure the success of your campaigns, such as conversion rates, customer acquisition cost, and return on investment (ROI).

Notable Case Studies:

  1. Netflix: Utilizes viewer data to inform content creation and recommendations. By analyzing viewing habits, they can predict what shows will be popular and tailor marketing efforts accordingly.

  2. Coca-Cola: Implemented a data-driven strategy by using social media analytics to understand consumer sentiment and preferences, leading to targeted advertising campaigns that resonate with their audience.

  3. Amazon: Leverages customer purchase data to personalize recommendations and optimize pricing strategies, resulting in increased sales and customer loyalty.

  4. Spotify: Uses data analytics to create personalized playlists and targeted marketing campaigns, enhancing user engagement and retention.

Recommendation: When developing your own data-driven marketing strategy, start with a clear goal and utilize the right tools to gather and analyze data. Regularly review and adjust your strategies based on the insights gained to continuously improve your marketing effectiveness.

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