True AI from vapor: Retail ROI with deep learning for retail
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NRF 2019: Retail's Big Show David Bessis, Founder and CEO, Tinyclues Francois Laxalt, Sr. Dir., Product Marketing, Tinyclues
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True AI from vapor: Retail ROI with deep learning for retail
- 1. TRUE AI FROM VAPOR: REAL ROI WITH DEEP LEARNING FOR RETAIL
- 2. 89% OF MARKETERS SAY THEY ARE PERSONALIZING EXPERIENCES AND MESSAGES ONLY 5% OF CONSUMERS SAY MESSAGE OFFERS ARE USUALLY WELL-TIMED WITH THEIR NEEDS Source: Forrester report Evolve Now To Personalization 2.0: Individualization; Forrester Data Consumer Technographics Global Online Benchmark Survey (Part 2), 2018
- 3. CUSTOMER MARKETING IS INCREDIBLY HARD YOU HAVE MILLIONS/BILLIONS OF DATA POINTS RELEVANCY PERSONALIZATION CUSTOMER EXPERIENCE DATA-ACTION GAP
- 4. HOW CAN YOU BRIDGE THE GAP?
- 5. MARTECH IS A COMPLEX LANDSCAPE
- 6. IT’S HARD TO BUILD INTELLIGENT CAMPAIGNS WHEN YOUR MARTECH STACK REQUIRES YOU TO MICRO-MANAGE SEGMENTS & RULES
- 7. Xbox Fifa 19’ $59.99 HOLIDAY GIFTS PURCHAS E HISTORY CUSTOMER SEGMENTS VALUE SIMILAR PRODUCT CATEGOR Y BROWSIN G HISTORY PRODUCT PAGE VISITORS TARGETING STILL HAS ROOM FOR IMPROVEMENT
- 8. HOW DO YOU BALANCE YOUR ENTIRE MARKETING PLAN?
- 9. FACE IT. YOU’VE BEEN PROGRAMMING A SWITCHBOARD.
- 10. IS THIS REALLY THE FUTURE?
- 11. HOW DOES AI FIT IN?
- 16. DEEP LEARNING CAN BRIDGE THE DATA-ACTION GAP YOU HAVE MILLIONS/BILLIONS OF DATA POINTS RELEVANCY PERSONALIZATION CUSTOMER EXPERIENCE DATA-ACTION GAP
- 17. Xbox Fifa 19’ $59.99 HOLIDAY GIFTS PURCHAS E HISTORY CUSTOMER SEGMENTS VALUE SIMILAR PRODUCT CATEGOR Y BROWSIN G HISTORY PRODUCT PAGE VISITORS THE OLD WAY OF TARGETING
- 18. HOW TRADITIONAL TARGETING SEES PAT WILL PAT BUY “FIFA 19” IN NOVEMBER? Gender = "F" Lives in the city RFM Segment = "High- value customer" Never purchased in this category -0.5% -4% +1% +3% -2% Email Address = "Patricia.Jones@gmail.com" Deep learning finds in your data that people with the email structure “firstname.lastname@gmail.com” are more likely to buy high-techor gaming items now. Video games are not very popular in Hamilton, Montana right now. A Hoverboard. Not the same category, but activates "kid stuff" latent feature in the Deep Learning. The theme was “Holidaysshopping guide”. Deep Learning detects that this link was aboutsomething involving the "Christmas" and "gaming" latent feature. Latent sociographics of high-end laptop users show they’re slightly more likely to buy video games for their kids or grandkids All attributes are calibrated and interpreted using patterns unique to your own business Zipcode = "59835" Bought SKU “TS9085” 5 months ago Clicked link #9 in your newsletter 2 weeks ago Browsed via Safari on latest MacBook Air + HUNDREDS of other "tiny clues" +0.3% -0.5% +3.2% +0.8% +1.2% +2.4% Conclusion: VERY LIKELY TO BUY. INCLUDE IN THE CAMPAIGN Age = "61" ATTRIBUTE IMPACT ATTRIBUTE IMPACTINTERPRETATION Conclusion: UNLIKELY TO BUY. DO NOT INCLUDE IN THE HOW DEEP LEARNING SEES PAT All attributes are calibrated and interpreted using patterns unique to your own business All attributes are calibrated and interpreted using patterns unique to your own business All attributes are calibrated and interpreted using patterns unique to your own business All attributes are calibrated and interpreted using patterns unique to your own business All attributes arecalibrated and interpretedusingpatternsuniquetoyourownbusiness All attributes arecalibrated and interpretedusingpatternsuniquetoyourownbusiness A chess game. Irrelevant. Bought SKU “MC8790” 2 months ago 0%
- 19. TINYCLUES SOLVES CAMPAIGN PLANNING & TARGETING WITH DEEP LEARNING
- 20. BASED ON DEEP LEARNING HOW TO DISTINGUISH TRUE AI FROM VAPOR? OFFERS MARKETERS A TOTALLY NEW EXPERIENCE
- 21. If your solution requires you to input complex rules in order to work, it’s not true AI.
- 22. If the UI gets more complex as you drill further into your marketing strategy, it’s not true AI.
- 23. If your AI provider asks you to format your data or apply your own logic to your data before integrating, it’s not true AI.
- 24. “AI-INSIDE” IS ABOUT ADDING 'YET-ANOTHER- FEATURE’ “AI-FIRST” IS ABOUT RETHINKING THE ENTIRE UX PRE-ENGINE ENGINE- INSIDE ENGINE-FIRST
- 25. SEAMLESS TINYCLUES IN A FEW WORDS SAAS BUILT FOR MARKETER S PROVEN IMPACT ACROSS ALL CHANNELS UP IN 2 WEEKS ANONYMIZED DATA DEEP LEARNING
- 26. BUILD THE BEST MARKETING PLAN FROM YOUR IDEAS & OBJECTIVES “We need to be very strong during the summer sales period. Who’s the best audience for our Facebook Ads on Weber BBQs?” “What’s the best audience for push notifications on our summer collection, in order to drive revenue online and in-store?” “We have 22 campaigns running next week; but no one should get more than 3 messages, and we want to distribute the messages based on highest potential to buy” ”Who should receive the Samsung TV offer? We need to target at least 1 million customers.” “Our range of handbags is niche AND strategic. We want a very small target of super buyers” “Does it make sense to send the following 2 campaigns on the same day: ‘Dishwashers’ and ‘Recipe books’?”
- 27. RETAILERS LOVE TINYCLUES -80%AVERAGE TIME TO CREATE CAMPAIGNS -19% +51%AVERAGE DECREASE IN UNSUBS AVERAGE INCREASE IN ENGAGEMENT +79%AVERAGE CAMPAIGN REVENUE UPLIFT
- 28. LACOSTE BOOSTING CAMPAIGN REVENUE FASHION / RETAIL "We have more than doubled our campaign revenue while finally being able to sell our strategic products ." +151% CAMPAIGN REVENUE MORE CAMPAIGNS LOWER UNSUBSCRIBE
- 29. HOLLAND AND BARRETT DRIVING MESSAGE RELEVANCY & CAMPAIGN REVENUE RETAIL -23% SENT EMAILS +19% OPEN RATE +27% CAMPAIGN REVENUE "Since we have started using Tinyclues, we have increased our campaign revenue by 27% while sending 23% less emails."
- 30. FNAC DARTY OPTIMIZING OMNICHANNEL CAMPAIGNS RETAIL "Tinyclues is at the very heart of our CRM, enabling my team to target and optimize more than 1500 campaigns per year, driving millions of revenue per year. The solution has a great impact on our strategy and revenue” +30% CAMPAIGN REVENUE +$8M ADDITIONAL REVENUE PER YEAR ON DIRECT MAIL CAMPAIGN
- 31. A LARGE AMERICAN JEWELRY RETAILER DRIVING CAMPAIGN REVENUE RETAIL +$1M IN STORE CAMPAIGN REVENUE
- 32. • Evaluate AI solutions based on their UX as well as their impact • If you need to normalize data to use a solution, it’s not a true AI solution. • AI will not replace marketers. It will enable them to do what they do best: focus on content and strategy. Actionable Takeaways from this session:
- 33. VISIT US AT BOOTH #643 TO LEARN MORE!
Hinweis der Redaktion
- This is an example of an email from fictional company, Games R Us, promoting Fifa 19’, to target this campaign, a retailer might use purchase history…
- So if you do all of this today, your marketing stack probably looks a bit like this: [show the slide with the messy, stressful-looking switchboard] Every time you add more functionality, you add more complexity. Every time you add more products to your stack, you increase the load on your team. These products promise “simplicity” but they add complexity in order to give you that “simplicity.” And let’s be clear: if you are segmenting your customers, you are using a switchboard. If you are operating from a messy excel sheet or its sleek technology equivalent, you are using a switchboard. If you are doing anything but inputting your strategic marketing goals and getting an output of actionable data/information, you are using a switchboard.
- The future of marketing needs deep learning if it is to truly simplify the process for marketers, clarify customer intent without annoying/fatiguing them, and drastically improve performance / revenue / engagement.
- What is Deep Learning? [Brief statement defining deep learning] What are the Advantages? Deep Learning can leverage all of your marketing data so you can inform all of your marketing decisions.
- You as a marketer have millions of data points and you’re trying to send relevant messages, with personalized content and trying to improve customer experience but there’s a clear disconnect between what you want to achieve, what you’re actually doing and what is perceived by your customers which makes customer marketing incredibly complex
- This is an example of an email from Macy’s promoting Fifa 19’, to target this campaign, a retailer might use purchase history…
- Now let’s see the difference between deep learning and data science in determining who is going to receive that Fifa 19’ email, we have here Pat…
- So this is what we're fixing. We're using AI to create a completely new experience for marketers where they can simply, in a calendar view, say on Monday I have a BBQ campaign but have also three different campaigns. Some of them going on emails, some of them going on Facebook, and it will instantly, in a matter of minutes, create the optimal audiences and the best campaign plan based on the true data points that you have. So you can at the same time send relevant messages that drives revenue. Finally, with Tinyclues, you can be Customer Centric & Business Centric.
- What is Deep Learning? [Brief statement defining deep learning] What are the Advantages? Deep Learning can leverage all of your marketing data so you can inform all of your marketing decisions.
- This is adding complexity to your stack, your team, and your strategy. Does it pay off in revenue, customer satisfaction and engagement?
- We’re here to share with you some tips we’ve learned along the way from working with retailers to target and plan their campaigns with deep learning
- Let’s go into a very detailed example of what we are doing with Lacoste. Many people know Lacoste through their polos. I think they are probably the biggest company in terms of selling polos, I think they sell 2 items every second. The thing is that it’s not a sustainable business strategy for them to sell only polos. So Lacoste has created a very diversified list of products and it’s a big challenge for them to drive revenue on these new products categories, because if you start to sell handbags, and you have a database of millions of people who came in to buy polos, it’s basically impossible without destroying your brand to spam everyone, all the polo buyers, with a newsletter about handbags. What becomes possible with Tinyclues is to find the right audience for these handbags campaigns. In terms of retargeting, you could try to sell the handbags to the people who have interacted with handbags before but the thing is, it’s a tiny fraction of the database, so you have basically no reach. What is possible with Tinyclues is to find the lookalikes of the people who recently bought Lacoste handbags and to find the right 10% of the database that is going to be interested by this handbag even though they never knew that Lacoste had handbags. And this kind of campaign performs more than twice better than the generic campaigns with their prior approach of targeting their messages. So they have been very happy with the impact that they saw, first on the French market, and we recently signed with them to go globally on their remaining countries. They are a very global company. I think they serve more than 100 countries.
- Let’s go into a very detailed example of what we are doing with Lacoste. Many people know Lacoste through their polos. I think they are probably the biggest company in terms of selling polos, I think they sell 2 items every second. The thing is that it’s not a sustainable business strategy for them to sell only polos. So Lacoste has created a very diversified list of products and it’s a big challenge for them to drive revenue on these new products categories, because if you start to sell handbags, and you have a database of millions of people who came in to buy polos, it’s basically impossible without destroying your brand to spam everyone, all the polo buyers, with a newsletter about handbags. What becomes possible with Tinyclues is to find the right audience for these handbags campaigns. In terms of retargeting, you could try to sell the handbags to the people who have interacted with handbags before but the thing is, it’s a tiny fraction of the database, so you have basically no reach. What is possible with Tinyclues is to find the lookalikes of the people who recently bought Lacoste handbags and to find the right 10% of the database that is going to be interested by this handbag even though they never knew that Lacoste had handbags. And this kind of campaign performs more than twice better than the generic campaigns with their prior approach of targeting their messages. So they have been very happy with the impact that they saw, first on the French market, and we recently signed with them to go globally on their remaining countries. They are a very global company. I think they serve more than 100 countries.
- Let’s go into a very detailed example of what we are doing with Lacoste. Many people know Lacoste through their polos. I think they are probably the biggest company in terms of selling polos, I think they sell 2 items every second. The thing is that it’s not a sustainable business strategy for them to sell only polos. So Lacoste has created a very diversified list of products and it’s a big challenge for them to drive revenue on these new products categories, because if you start to sell handbags, and you have a database of millions of people who came in to buy polos, it’s basically impossible without destroying your brand to spam everyone, all the polo buyers, with a newsletter about handbags. What becomes possible with Tinyclues is to find the right audience for these handbags campaigns. In terms of retargeting, you could try to sell the handbags to the people who have interacted with handbags before but the thing is, it’s a tiny fraction of the database, so you have basically no reach. What is possible with Tinyclues is to find the lookalikes of the people who recently bought Lacoste handbags and to find the right 10% of the database that is going to be interested by this handbag even though they never knew that Lacoste had handbags. And this kind of campaign performs more than twice better than the generic campaigns with their prior approach of targeting their messages. So they have been very happy with the impact that they saw, first on the French market, and we recently signed with them to go globally on their remaining countries. They are a very global company. I think they serve more than 100 countries.
- Let’s go into a very detailed example of what we are doing with Lacoste. Many people know Lacoste through their polos. I think they are probably the biggest company in terms of selling polos, I think they sell 2 items every second. The thing is that it’s not a sustainable business strategy for them to sell only polos. So Lacoste has created a very diversified list of products and it’s a big challenge for them to drive revenue on these new products categories, because if you start to sell handbags, and you have a database of millions of people who came in to buy polos, it’s basically impossible without destroying your brand to spam everyone, all the polo buyers, with a newsletter about handbags. What becomes possible with Tinyclues is to find the right audience for these handbags campaigns. In terms of retargeting, you could try to sell the handbags to the people who have interacted with handbags before but the thing is, it’s a tiny fraction of the database, so you have basically no reach. What is possible with Tinyclues is to find the lookalikes of the people who recently bought Lacoste handbags and to find the right 10% of the database that is going to be interested by this handbag even though they never knew that Lacoste had handbags. And this kind of campaign performs more than twice better than the generic campaigns with their prior approach of targeting their messages. So they have been very happy with the impact that they saw, first on the French market, and we recently signed with them to go globally on their remaining countries. They are a very global company. I think they serve more than 100 countries.