How to Communicate with Your Customers by Putti Cakes Founder
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As a product manager or a startup founder, you know you need to talk to your customers; Everyone talks about it enough! There are endless articles, books, blogs and talks from well respected experts that repeat that same message: "Talk to your customers". And yet, products still fail because we're so focused on talking to our customers, we forget to listen and understand them.
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How to Communicate with Your Customers by Putti Cakes Founder
- 1. How to Communicate with Your Customers by Putti Cakes Founder www.productschool.com
- 2. FREE INVITE Join 23,000+ Product Managers on
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- 10. › Today’s Goal › The Problem › Key Factors › Common Techniques › Q&A Agenda 10
- 11. ROLL CALL Who’s in “da house”? 11
- 13. Product Team of 1 13
- 16. What are you expecting? What do you want to get out of this? 16
- 17. 17
- 18. … and why should I care? 18 WHAT IS THIS ALL ABOUT?
- 19. 19
- 20. 20
- 21. 21
- 22. MY TARGET 22
- 24. › Customer research 101 › Technique How-To › New techniques What this talk isn’t... 24
- 25. So who the f**k are you … and why should I listen to you? 25
- 26. 26
- 28. 28
- 30. 30
- 31. 31 Hmmm...
- 32. Consulting! 32
- 33. › Life and Pensions › Defence › Telecoms › Video Streaming › Ticketing › Music › Fashion › Animal Pharma… etc Where I’ve done it 33
- 34. 34
- 35. › Launched new products › Startups and giants › Been there, done it Why does that make you qualified? 35
- 36. › Full-time focus › Develop product strategy › Teaching & Training › Mentorship Why does that make you qualified? 36
- 37. › Bring order to chaotic startups › Bring chaos to “ordered” corporations To simplify... 37
- 38. How to build a product? 38
- 39. Typical steps DEFINE DESIGN BUILD 39
- 40. What does this look like? DEFINE Idea forms Some discussion Write up spec BUILD Brief dev team Create backlog Create project plan DESIGN Brief designers Create mockups Brief technical lead High-level spec 40 Feedback/analytics Market research Problem brief Collaborative design User testing Iterative releases Hypothesis testing
- 41. Expectation? 41
- 42. 42
- 43. Reality 43
- 44. 44
- 46. › Low product uptake › Decent usage, but no money › General indifference Common outcomes 46
- 47. Where did we go wrong? 47
- 49. PROBLEM Identify problem Understand problem The key challenges SOLUTION Identify solution Tailor solution 49
- 50. PROBLEM Identify problem Understand problem What people focus on SOLUTION Identify solution Tailor solution 50
- 51. PROBLEM Identify problem Understand problem What they should be focused on SOLUTION Identify solution Tailor solution 51
- 52. YOU CAN’T CREATE CUSTOMER NEEDS! … or change the details around those needs 52
- 53. WE CAN IDENTIFY A PROBLEM But we don’t understand how to solve it!!! 53
- 54. › Customer Interviews › Surveys › Landing page MVP › Concierge MVP › Wizard of Oz MVP › Fake Door MVP › “Core” MVP Some common techniques 54
- 55. Some things to bear in mind... 55
- 56. › Understand both › Levels of confidence › Tailor to your situation: › Complexity of problem › Complexity of solution › Engineering resource 56 Problem vs Solution
- 57. New Product More unknowns Right problem? Harder to find “users” Dev constraints New Product vs New Feature New Feature More data/feedback Problem details? Existing users to draw on Less dev constraints 57
- 58. Qualitative Customer Interviews, usability testing, etc Understand the why Not statistically valid Generally not scalable Qualitative vs Quantitative Quantitative Analytics, (some) surveys, etc Measure the what Statistically valid Scalable to larger numbers 58
- 59. › Customer Interviews › Surveys › Landing Page MVP › Concierge MVP › Wizard of Oz MVP › Fake door MVP › User Testing › Core MVP What are the techniques 59
- 61. › 1-1 chat with customer › Problem focused › Qualitative › Key points: › Avoid bias or leading questions › Talk to at least 10 people › Ask screening questions › Reverse engineer questions Customer Interviews 61
- 62. › Use at start › Validate problem › Existence › Details › Mandatory › Use on new product or new feature When and how to use 62
- 63. Surveys 63
- 64. › Could be quant or qual › Could be problem or solution › In-person or digital › Key points › Avoid leading/biased questions › Less suited for quant › Keep it short! 5 questions or less Surveys 64
- 65. When and how to use 65 › Problem focused › After customer interviews › Use above to guide questions › Increase confidence in learnings › Solution focused › Get feedback on a feature › Can target specific users › Compliments analytics Caution: open-ended = manual work!
- 67. › Create fake product page › Validate problem by measuring “something” › Saves build time › Helps Marketing › Key points: › Clear messaging › Clear CTA › Bold, but not dodgy Landing Page 67
- 68. When and how to use 68 › Use at start › Validate problem exists › Some solution testing › New products
- 69. Concierge MVP 69
- 70. › Do it yourself › Problem + Solution › Qualitative › Key points › Ask questions › Be hands-on with user › Track priority vs effort Concierge MVP 70
- 71. When and how to use 71 › After problem research › Before build › New Products › Complicated problems/solutions › Know when to move on
- 72. Wizard of Oz MVP 72
- 73. › Concierge but black box › Solution focused › Not scalable › Key points › Review user sessions › Track priority vs effort › Step-by-step automation Wizard of Oz MVP 73
- 74. When and how to use 74 › After problem understood › After customer interviews? › After Concierge MVP? › Follow up with customer interviews/surveys › New products or new features › Problem backog => Step-by-step automation
- 75. Other techniques … in less detail 75
- 76. Fake Door MVP 76
- 77. › Validate problem by measuring “clicks” › Very light touch solution, i.e. entry point › For existing products › Feature doesn’t exist › Key points: › Analytics are key › Be bold! › Appreciative tone › Don’t be dodgy Fake Door MVP 77
- 79. › Pure solution testing › Testing design with real users › Well understood › Pre build › Paper vs digital Usability Testing 79
- 80. Core MVP 80
- 81. › Lots of “MVPs” › Concierge MVP › Landing page MVP › Wizard of Oz MVP › MVP = Viable › MVP = Product › Concierge experiment › Does the product exist? MVP Rant 81
- 82. › Iterating to find MVP › Not “first version” › Start small, i.e. alpha/beta › Iterate towards larger release › Build on other techniques › Ultimate goal: prove product-market fit “Actual” MVP 82
- 83. Wrapping up What we’ve learnt... 83
- 84. › Understand the problem › Always do customer interviews › Favour experiments › Do what works for you Wrapping up 84
- 85. › Run workshops › Techniques in depth › Practical focus › Finalising dates/venue › Just ask If you want more... 85
- 88. › Training › Product Strategy › Product Development Process › Mentorship › Specific question If you need... 88
- 89. 89
- 90. 90
- 91. I need your help! This will only take a sec... 91
- 92. I need your help 92
- 93. › Grab Pen and Paper › Rate this talk 0-10 › Email address for newsletter › Any feedback I need your help 93
- 94. › Please be honest › Feedback helps us improve :) I need your help 94
- 95. Thank You Over and out... 95
- 96. Part-time Product Management Courses in San Francisco, Silicon Valley, Los Angeles, New York, Austin, Boston, Seattle, Chicago, Denver, London, Toronto www.productschool.com
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- notes
- Clarify purpose of the talk so everyone understands up front Bit more info on the problem so we’re clear on what we’re solving Some key factors to consider to frame these techniques Run through techniques Classic Q&A
- Want to understand audience
- Product manager in a team of product managers?
- The only product person in entire company
- Looking to make a change into Product Management
- Something else?
- Recognise the true need and what you’re trying to achieve Not perpetuate the usual talking points Process is about people - so make sure people feel happy
- Show of hands - who has heard this in a talk? Been to countless talks - “talk to your customers”
- What actually happens People are biased
- Most common: user testing Tests the usability of a design of a solution No insights into customer behaviour
- Key message: customer understanding Don’t just listen, understand What does understanding mean?
- Key message: customer understanding Don’t just listen, understand What does understanding mean?
- Not a beginner’s guide to customer research; emphasising where people go wrong Not a guide to techniques; more about the key points when considering whether to use No new Navin-branded techniques;existing ones are pretty decent for most scenarios
- Prob thinking - who is this guy What makes me qualified to talk about this My answer is… woah, what’s with the attitude
- Been a developer C++, HTML/CSS, Javascript, Perl, Java, etc
- Been a technical product manager Hands on with really technical niche products
- Was a business analyst but who was also product manager
- A fully fledged pure product manager
- Last couple of roles have been leading product teams Hiring new members Training Setting product strategy
- Got to the top What do I do now?
- Gun for hire Go where I’m needed Usually cus things are bad
- Gun for hire Go where I’m needed Usually cus things are bad
- This is my day job now Work at top-level to develop product strategy Help teams that are struggling to get better Teach at Product School Do training and workshops Mentor product managers, CEO, etc
- Problem definition - what are we trying to do Design - how do we solve this Build - create product More complicated; iterative approaches Release and feedback also on there
- Define Idea usually comes from senior stakeholder or business “strategy” Might be some discussion - head of product, head of engineering, etc High-level problem spec Design Make sure designers understand First pass at design Get technical feedback Updated spec Build Do Dev understand More detailed specs Plan of release Bonus Making sure problem exists w/ feedback/research Define as problem instead of feature Bring tech in earlier, maybe even rest of company Check the design Earlier release = earlier feedback Design tests to check assumptions
- Product goes out; people wait with baited breath
- Big success!!!!
- But what actually happens
- Yeah, not quite what we expected
- No-one is using the product No-one is buying the product Users look at it and shrug
- We don’t build products for the sake of it So what did we do or not do that led us here?
- First, remember what product success We have a list of problems that users might have We have a list of solutions that could fix those problems A good product brings the right solution to the right problem
- Two parts to the problem Did we identify a genuine problem for e.g. do people want to order food at night Do we understand the details of the problem, for e.g. do people want to explore, do they just want the same stuff, convenience vs price vs quality (or both), if so, when do either happen? Similarly two parts to the solution Did we pick the right solution, is it an app that lets your order food Did we target the solution to the problem (using those understandings), is it a “top rated” list with filters, is it a browse by cuisine?
- Everyone focuses on solution Easier to understand Easier to plan; action Less ambiguity That’s why people jump straight to design and user testing
- People make assumptions People misunderstand what people need
- I would argue that companies are getting better at knowing there’s a problem Discount the startups that just go head first into it I hear pitches and the top level seems reasonable It’s when they go into the detail my product senses tingle and I cringe Because at that point, they’re like, yes, I know what they need and go off arrogance One startup founder, I tried to help him, but he would rather take funding and build something for 3 months before first release, rather than try one of the techniques listed. Which would cost him nothing but time
- Here are some of the techniques you can use Will run through them in more detail
- Keep these in mind when deciding what to do Use these to understand the techniques better
- Need to understand both Have to understand problem and understand how solution will fix problem If you don’t, chances of success = low Not a perfect science Never going to be like, yes, I am 100% sure Don’t take too long trying to be perfect Consider different factors If problem is complex, spend more time, but if easy don’t dilly dally If solution is problem, spend more time If easy access to devs, consider a more experimental approach of trying different things
- New product You’re starting from scratch, no data or feedback (unless you get it) Do you even have a problem worth solving? How do you get users? Are they even the right users? Who are your users? Potentially no developers, or expensive outsourcing. No existing product infrastructure to “plug” into New Feature Existing product with analytics, customer feedback, etc so more clarity More focus on understanding the detail of the problem Users well understood, easier to reach out and get details Existing team and product infrastructure
- Qual Name suggests - quality Examples are customer interviews, usability testing Focus on insights, i.e. why people do this Not statistically valid so don’t assume applies to everyone Not scalable because labour intensive Quant Name suggests - all about quantity of data points Ex like analytics, surveys (in some cases, as I’ll cover later) More about the what, doesn’t tell you why Stat valid as there are far more data points, or rather you have to collect meaningful quantity of data Scalable as it’s more tech based, i.e. send standard survey with options, check analytics data, etc
- Here are some of the most common techniques Let’s run through them now
- Conversation with customer Open-ended questions Normally 1-1 Best in person Problem focused Usual mistake is people bring solutions Identify whether target market has problem If do, delve into detail Qualitative You get feedback you need to process Look for insights, not stats Applies to both new product and features (but if features, most likely exploring the details of the problem) Key points Don’t push people down a path; don’t use yes/no questions. Use phrases. A good way is to ask about the last time they did something, so it’s a specific story 10 people seems to be a good number. It’s not stats but gives you idea. If nobody has the problem, did you screen properly. If everyone has problem, yay! Also think about where you’re gonna find these peopel Screen screen screen. Make sure you’re talking to the right people Typically you have your answer, your assumption. Think about how to phrase a question that would result in that answer. And then ask it without prompting. If you’ve asked and they don’t, then can prompt, ask how it compares to what they said, why they didn’t bring it up, etc
- Always use at the start, too late otherwise You can use to validate problem and details, though you need to find the right people
- Could be quant if you ask open questions gathering feedback Could be qual if you ask multiple choice since you can collate results Could be problem if you ask about their lives, behaviours, etc Could be solution if you’re asking about a product they’re using Could do it in-person or could be digital Key points Same principles apply; if you’re asking a question, don’t make it biased. Neutral language, not so much yes/no. Ask them to rank lists, etc I think it loses it’s power for quant because either you’re not there or you’re not exploring why they feel that way Don’t put too much in or you’ll never get responses!
- Problem focused Make sure you’ve collected good insights first, unless you can’t Use this info to guide your questions Adds some stats weight to what you’ve found so far Solution focused Do after a release to check perception of a feature Can be specific with people who did some set of behaviours Analytics doesn’t give you the why, surveys can give you that
- Also called pre-order page Fake a product Make people think it exists Provide whatever you need to convince them All about whether the problem exists Quant as you’re getting numbers “Something” is some signal that users want this product, could be signing up, could be clicking buy now Touches on solution because you need to describe the product, for eg app, or service, etc Don’t have to spend time building product Helps your marketing team Testing your message to understand what works Gathering future users info Key points Test your message, make sure people understand it. User test it Clear signal for success, signup, book this, buy this, whatever OK to leave your comfort zone, it’s scary. But stay true, There’s no obligation here, but don’t take money, don’t steal details and misuse them, etc. And not your final brand
- Early stage Pre-build so that you’re not wasting time Use the learnings from customer interviews Make sure problem exists; doesn’t tell you details of problem It gives you an idea if the top-level description of what you’re offering is appeasing, but don’t get too caught up in it. Long way to go! Use on new products. Could do with an existing, but doesn’t make sense since you’re not saving dev time. And new features prob fit into an existing product with your existing features. Maybe if it’s a completely new product within an eco system?
- Provide the solution You talk directly to the user You do whatever they want for them For e.g. food box subscription service - be their weekly shoppers Combination of both You still talk to customer, understand their problem in detail You also try out the solution manually, learn the inside and out Still gathering info on both problem and solution You’re learning from customer You’re learning from doing Not scalable to large numbers Key points Asking questions = knowledge. You’ll see weird things and you can and should ask otherwise you’re wasting your time You should do this, learn as much as directly as possible Make sure you record which things are important to users, which aren’t, and understand how complicated certain things are. This all adds up to give you an idea of what you should build, when and why
- Do your customer interviews first, maybe even landing page experiments Do it before building so that you can learn about the solution, save time Obviously. New features are a bit harder because you already have a product, though not impossible. Will come to a better technique next If you have particularly complex problems and/or solutions, this helps flesh out a lot of the details with your focus. Otherwise you never know what to build and it fucks with you and causes stress To learn about the problem. This doesn’t last forever, recognise you need a level of confidence and then you move on. Handily, next step could be the next technique
- Same as previous technique But you take a step back Replace you with thin product layer Customer interacts with product as they would Don’t realise it’s done manually underneath You’re looking more at the solution now You’re still learning about how to solve need You’re testing how the user interacts with the product But you can’t ask questions directly about the why Still not scalable due to manual nature of solution Key points Learn about how user interacts by using tools like full story that let you playback a user session. You still have small numbers so you should be looking at that data Just as before, use your learnings about the solution to determine what you need to build next and why Since we’re comfortable with the problem, we can start building the solution. Good approach is to think about the most painful piece and automate it. If that lets you scale out the product, even better :)
- Need to be clear on problem before you go down this road Could be immediately after customer research because problem isn’t complicated Could be leading on from concierge MVP If you notice something weird, don’t be afraid to go back and ask people. This is because you’re not getting the same insights as if you were talking to people New products, obvs, but easier for new feature as you can fake the user interaction layer. For e.g. at DICE, we had new seat maps. Had no time or clue how to build a seat allocation algorithm. Did experiment for a couple of events, just faked the front-end. It just came to a spreadsheet. Interns would manually process and try to make people fit in. We learnt from it. Want to repeat that point again. You can build the product step by step. Doesn’t mean make it a frankenstein, but with a good dev team, this is easier. You build only what you need but in a way you can extend. It might take a bit longer but at each point, you’re solving a problem. Keep in mind final goal and figure out how you get there and update as you learn.
- I’ll cover other techniques for completeness, but in less detail These are pretty well understood and for me, not as important as the others which can really improve the way you understand the problem, which is my central point
- Similar to landing page, measuring whether anyone wants this You’re kinda testing the start of the solution, i.e. the trigger that gets them there For existing products, i.e. ties into a place that people already come to Pre-build, you save time by checking whether anyone cares or not Key points You need to have your analytics sorted, that’s what tells you if it succeeded or not Similar to landing page, be bold, don’t be afraid Get the tone right. Be appreciative. You can be honest that this was an experiment. Most people are forgiving Don’t try to trick people, i.e. don’t be a dick
- You’re not really understanding the problem because you’re telling users what scenario But it is good to check usability issues with the design Everyone knows how to do this; pretty well documented It’s still saving time so that you can avoid costly dev mistakes Different ways to do this. Complicated paper prototypes vs static mockups vs interactive clickable prototypes
- Total buzz word, potentially confusing Personal opinion, but Viable - means something that can stand on its own feet Product - something that exists Everyone just thinks of it as first iteration Prefer the phrase experiment That’s all it You learn something, but you can’t make money Best question, does something exist after you finish or is it learning? As we talked about, MVP is more of an iterative building process to find the right point, not just the first iteration
- It’s an iterative process. I don’t think you really say here’s my MVP and you build it and that’s it. It’s saying you have confidence in problem and solution, here’s your assumption, now let’s build to that release, try it out and see if it succeeds, if not we continue Not the first version. Everyone things about it that way. That’s kinda BS. It needs to have a coherent core, not just “something” You’re building towards a larger release in steps You need info from other techniques. This isn’t teaching you about problem vs solution. It’s a way to derisk how you go about building things Product Market fit - that’s your goal. Understanding that and proving it so that you can now work out how to scale.
- If only one thing, remember that you need to understand the problem in more depth Customer interviews are mandatory, if you can’t do this, it means you’re not understanding your customers Experiments are much cheaper ways of learning. You get to see and interact with users without taking a lot of dev time. Don’t be beholden to all these techniques. Touched apon when to use, think about what works for you and use an approach that fits your situation
- Really found that this and other topics really not covered, been asked by students so running workshops Do other things like metrics, process, product strategy, etc. This is one of them. Will run through what we discussed in more detail But most importantly, it’s practical. For me, that’s the key. You can read this stuff, but it doesn’t settle. Have to create these things with support I’m sorting out venues now and therefore dates, but looking like within the next couple of months Feel free to ask me for more info; leave your email address or take a business card and email me :)
- Been a developer C++, HTML/CSS, Javascript, Perl, Java, etc
- Cards are on table Running MVT test on designs
- All about delivering value Feedback is like gold dust Fancy an experiment