First order product management is when you are thinking of immediate effect of your action. 2nd order product management is thinking everything else that ultimately have a long term impact on your core metric.
For every change in product, there is always a short term impact on all metrics. There are metrics that you are either not measuring or you are not able to find a direct correlation with. We generally shy away from measuring such metrics because they are either beyond the standard analytics tools or it is a qualitative data that cannot be measured. Such metrics have detrimental to the long term sustainability of the product.
Here are few examples:
Freecharge coupons – When Freecharge was launched in 2010, there was a limit to the amount of coupons users were issued for every transaction. This created a virtual scarcity and hence value for the coupons. That value for coupons was the basic differentiator between a newspaper flyer or retailmenot.com kind of website and Freecharge. Our estimates said that the coupon redemption rate was upwards of 50%. A number unheard of for coupons. In 2011-12, the sites that copied freecharge, like Paytm, were offering unlimited amount of coupons. Freecharge was losing the traffic war with Paytm because of bad SEO, non-availability of a good mobile site and heavy discounting. Amongst many things that was changed, freecharge started giving unlimited number of coupons. That was the point of death for freecharge. It had lost its initial value proposition and was now chasing a base metrics of number of active users but with a monetization engine that was losing its value. Unlike Paytm that created wallet, mall and bank on the back of recharge based acquired users, freecharge, as a product, had no new vision. There was little contribution of unlimited coupons on growing the user base but definitely the long term impact was adverse on the core product. The original business model of freecharge was similar to American Express, “an exclusive discounts club” but over time that was dead. Today Freecharge, as a product, stands for nothing.
Mithai and bakery shop discounting – A lot of Bakery and Mithai shops discount the highly perishable products in late evening hours. The idea is to make some money instead of letting it perish and additionally spend money to dispose it. When a bakery introduces this, there is a direct impact on topline. Over the long run, customers see this as a regular feature and delay the purchase untill late hours. As a result, the number of products being sold is same but now at a lower price.
This discounting model is good for bakeries inside hotels where the audience is not regular and the display is highly visible, hence creating an impulse purchase but not for those attracting residents of a neighbourhood.
Dominos – I believe, this brand in India has exploited coupons the most. The coupons were so abundant in early 2010’s that it would look stupid to order Dominos without coupons. Short term sales went up but long term value went down. As a result, when there was no coupon, we would order from a “premium” place. This isn’t great for a brand, unless they want that perception.Regular discounts are not a marketing activity but a product feature. A lot of product managers assume they have found a product-market fit because the product has a huge adoption when some discount is offered. They assume that the discount can be removed later with no impact on adoption. These are good tricks to test a hypothesis or raise venture capital but not for a building a sustainable product. The product-market fit you know is actually product-price-market fit.When the price changes, so does your target audience and perceived value of the product.
Affiliate systems – Amazon in US pays 4-8% fee for affiliate marketing. The direct impact is that it brings sales but as a second order benefit it also improves SEO and accelerates word-of-mouth, because most affiliates are influencers. Both of these second order benefits are not measurable directly. Oh BTW, I just launched Refrens.com – an affiliate management system for offline sales channels.
Second order product management is like playing chess. You have to think of next 3-10 moves. One good way to visualize second order impact of product management decisions is to think in terms of relative metrics, rate or percentages, instead of absolute numbers. Like, revenue per user instead of absolute revenue or CTR instead of total traffic.
If you are offering free, freemium or free trial of your product, read this old post to understand what to use when. The Linkedin example at the end might be useful.
There are 3 kinds of business softwares, that do 2 things viz., save you money (bottom line), or bring you more money (top line).
Software that saves you money – Software that saves you money directly tend to optimize your procurement viz. server costs, power costs etc. These are generally an upgraded technology or a smart resource monitoring system.
Value proposition is very clear. Customer invests X amount in the software and any directly measurable saving above X is a win.
There shouldn’t be human on the client side to manage the new system. Installation etc. must be handled by seller else selling becomes tougher.
Easy to sell in any region but generally has to be bundled with or piggy back on a bigger system. Like a resource monitoring system on top a server system.
Software that saves you money through saving human time. These softwares bring money saving at second degree. They decrease manpower requirement which ultimately results in money saving. Most business softwares fall in this category as they bring some form of workflow automation.
Being able to show the value proposition is tougher as it is difficult for a lot of businesses to fire manpower. In businesses where only one person’s time is saved because of your software, it’s of little use as they cannot fire half of that resource.
Manpower training is required. Must be done by the seller. Generally the decision maker isn’t using the software but his sub-ordinates are. There is a shyness to adopt new system hence they complain. New systems also results in fall in productivity temporarily due to steep learning curve and some the software is never adopted. When done right, this also creates a lock in.
Easier to sell in regions where avg. wages are high. India is tough country for such software.
Software that brings you more money – These are generally “intelligent” softwares. A/B test, targeting etc.
The management and employees’ tendency to adapt such a software is always higher as the affected metrics is also a key metrics for any business.
A lot of work flow softwares also fall in this category, like a notification tool that reaches out to your customers for upsell. The incremental revenue in such a case is only the difference between doing no marketing vs. doing some marketing. A good software in such a case should add intelligence by telling you what is the right time to send notifications to each customer, else the software would soon be a commodity. A tool that brings the benefit of network survives this game better.
Sell it to sales/marketing team. Keep it as independent as possible so that other departments do not interfere during adoption.
Webengage, the marketing automation software, started as Webklipper, an annotation tool that would save time in design feedback. It later converted to a feedback capturing app. A feedback capturing app is only useful until you have team/resources to act on the feedback. For the last few years, Webengage is a marketing automation tool that pitches higher conversion rate as its USP. This value proposition appeals to a wider audience.
I am going to discuss “party rounds” here. This is generally the 1st or 2nd round of funding for Indian startups when they set out to raise through references or funding platforms like Letsventure, IAN, Angelist etc.
This is only meant to set expectations right for first time fund raisers. Some of you might find it controversial to discuss some of this publicly but it’s all plain honest observation.
If you are planning to raise INR 75L. Always say INR 50L in the market. Read on to know why.
Raising INR 50L to 5Cr is possible in such party rounds. Lowest I have seen is INR25L.
Have a star investor (brand name) or lead investor (more money) who has covered 30-60% of the round, so that there is momentum to show when you hit the road. This is where announcing a lower target helps. Always show momentum during fund raise. It helps create FOMO.
There are only 2 reason why you get investment viz. history with the investor and momentum in the product. First investor is almost always based on history.
Keep refining your pitch after every pitch. A lot of NO’s generally means bad team (lack of history, trust, affiliations) or bad market (too difficult to visualize). It’s never about the product at this stage. People have limitations with respect to what markets they can analyse. They trust the lead investor for other markets.
Investors are easy to convince when they are also potential target customers. A premium cab service is easier to raise for, even though it might have limited market, as opposed to a low cost water cooling device which has a bigger market in India. Investors are not wrong when they turn you down, everyone has limitations to what they can understand. Bank upon your current investors to open more doors for you. Referrals always help.
There is always a flavour of the season in investments. If there is a fresh acquisition in your industry, or a star investor has invested in your competitor, your industry will be the new flavour of the season. More competitors is good at this stage, it helps establish that there is a market. Herd mentality is for real.
As low as 10% dilution is possible at this stage. Don’t go beyond 33% dilution, you will either have money lying in the bank or you would be burning unnecessarily.
Always pitch with pre-money valuation. Post-money valuation will defer based on exact round size.
Never give investors a range for valuation or round size. Always give definite numbers. It helps. It is OK to change round size by 10-15% later, NOT OK to change pre-money valuation. Be sure of what you want to optimise for(read this) in this round.
Keep paper work ready. Ask for cheque or transfer to an escrow account immediately. Angel investments are impulse purchases. Once they are enticed, don’t give them time to think or discuss much with friends/family.
INR 5-25L is the general range from individuals. I have seen as low as INR 60K. I have heard of maximum INR 1Cr from an individual.
Try and get commitments of upto INR 1cr. Then start making the final closure. You will have a 20% dropout at this point. Which will set you around your initial target.
Close the current round when you hit the target 80-120%. You will never have exact round size.
If this is your first round, open new a round immediately after this. Keep feeding your current set of on-boarded investors with momentum news. Give them something to brag about in social gatherings or online. Keep the language simple. Mostly, news about star name client onboarding helps. People love to reduce their degree of separation from “bigger people”. At this stage your startup is nothing more than a diamond necklace worn by a rich aunty at the Kitty Party. Sparkle. Give her reasons to get noticed. She will attract more investors for you. This is easy money, coming through envy. Don’t say no even if you still have 90% of the money from the last round. Ask for a 50-100% premium from your last round or do a convertible note. Capitalise on FOMO.
Never say no to an incoming cheque. Most money will come to you when you need it least.
Target to raise for 18 Months. For your next round, keep a milestone that you plan to hit in 9 months. You will always take 18months. Hit the road again in 12 months. 6 months of dedicated follow up to close a funding round is normal.
Star investors do the least amount of diligence. They are generally betting on the market and you seem to be a trustable salesman. Your startup is still a show piece diamond necklace.
Smaller unknown investors come on-board because they want to be in the same kitty party as this star investor. They are also under the impression that the star investor must have done due diligence. Mostly that never happens if this is the first round.
At this stage, due diligence is a name-sake signature to keep the kitty party happy. The startup pays for the due diligence. You, as founder, can always threaten the auditor to not pay if diligence report is not in your favour. It is always in your favour. Incase of big VCs, the DD is paid for by the startup only if the investment happens. That is still sane.
Don’t ever request for NDA’s. No one likes it and you won’t have energy to sue anyone incase of a breach. Your pitch-deck will be floating in the market. Your competitors will have access to it. You can’t help it.
News about this will leak. The analyst at a VC firm did it. Or the star investor wore you too early to the kitty party. You can’t help it.
There are no standard laws. Everything is negotiable.
Don’t complain about anything while you are raising money. People like to associate with positive people, keep your social media clean. A lot of first time eye-opening moments will be experienced. Learn and move on. Don’t complain.
After you have announced the closer of round, there will be a lot of people wanting to join in with small amount. This happens when the other angels spread the word at parties. Its good to keep a weeks buffer between when you announce round is closed and when you actually start doing the paper work.
In most cases, entrepreneurs are trying to optimize for 2 or all 3 variables and that is what takes away most of the time. If you only optimize for 1 of the 3 metrics, suddenly the problem looks simple. And that may be the difference between life and death of your startup. Which metrics to optimize is dependent on which stage you are at. The only time you can optimize for valuation is when you don’t need the money.
As simple as it sounds, most entrepreneurs with a decent product, fail to identify the priority order.
In general, the 3 choices viz. affiliation, short term quantity and long term value are present in every decision.
For job – Brand name, work experience, salary. – When should you optimize for what?
For Sales – The customer’s brand name, the invoice size, the gross margin.
Knowing what you want out of the deal helps you speed up.
A popular restaurant wants users to order through apps like Zomato or Swiggy because taking telephonic orders in busy hours requires lots of man power. Whereas, a new restaurant latches on to these apps for the new customers they bring.
The first set of restaurant are coming for the tool whereas the second set is coming for the network. Should the commission pricing be same for both? Does it help to know the segmentation and hence approach both set of customers differently? From what I know of last year, Zomato was treating them differently.
Take another example of Star Network vs. TVF on Youtube. Star’s content is popular and has a ready set of viewers. By being on Youtube, Star was giving more to Youtube than vice versa. May be YouTube did not care for the differentiation much, so Star network launched HotStar. TVF has an app but the Youtube channel is what the audience prefers. It’s like a small restaurant trying to make its own app and hoping to compete with Zomato. Possible to save some commission but not worth the effort.
In offline world, popular retail brands like BizBazaar or McDonald’s have the ability to drive footfalls to any corner of the city. Should a mall charge them the same rent as regular brands? They don’t.
On a related note, does a businessman in Delhi take car loan for the same reason as a techie in Bangalore. No money vs. no white-money. Will their interest paying capacity be same? Which of the two is looking for convenience of assisted service vs. lower price of online buying?
Does the person making a CoD order on Flipkart really not have a debit card? Are such users willing to pay a higher price because it helps them consume untaxed money?
It helps to know the real reason why your product is being used. The pricing and User Experience metrics will change when you know that.
Any exchange, crypto or otherwise, has to find the correct brokerage model to balance network growth and revenue growth. There are 3 parameters to look at while deciding the most suitable model – User friction, market liquidity and transaction execution.
Buyer and seller both pay equal – In India, Coinsecure and Zebpay follow this model. User friction exists for both the parties, revenue burden is distributed but liquidity in market will always be low.
Maker and Taker, both pay equal – Maker/Taker differentiation became popular in crypto world. Primarily, this separates liquidity creator from the liquidity absorber. Works in similar way as above for all 3 parameters.
Only taker pays – GDax from Coinbase follows this model. Only transactions that absorb the current liquidity from the exchange have to pay. This model does incentivise creating liquidity in the market but there are too little transactions that get executed as the taker has to pay a penalty (the fee). There is too much anxiety with respect to being a taker vs. a maker. If you become a taker, you pay a fee which you wouldn’t need to pay if there was a cent of a difference. If you become a maker and wait, the market might turn against you and transaction might never happen.
Only Buyer pays – Koinex in India follows this model. Seller is incentivised to create liquidity in the market. Seller has 0 anxiety. Buyer pays a little fee, which is fine as he was anyways looking to invest in the instrument. As compared to Gdax model, there are more transactions that get executed here, with the same revenue generation per transaction, as one side is still paying.
In ecommerce marketplace, it’s always the seller who pays. On the contrary, Airbnb makes the buyer pay for the transaction/convenience fee, over and above the tag price. Would Airbnb do more transactions if the tag price was the final payment amount for the consumer?
When enabling a transaction becomes commodity, the value of marketplace lies in enabling trust. Trust that the marketplace will connect the consumer with worthy service provider. Feedback from past users are the key to building this trust. I have written about this in detail back in 2013 for various industries.
There are few practices in feedback collection that are being overlooked by popular marketplaces that will end up creating less trustable profiles in the long run.
Forced and Untimely feedback: From what I recall, Uber started this practice of collecting feedback about previous transaction at the beginning of new transaction. While it is designed to collect feedback at the end of the current transaction, users have no reason to look at the app in the end. What are the chances that I actually remember my last transaction unless it was horribly bad? What are the chances that I want to pause for a while and put efforts to give a genuine rating. At this moment, the feedback screen is just a pop up with a skip button camouflaged in the rating stars. I wouldn’t want to sound too judgemental and there is always room for improvement so I give a 4 star. Most users end up giving 4 or 5, because thinking, at that moment when you are waiting to book a ride, is too much cognitive load.
While cab rides are commodity and all factors are hygiene factors (from Herzberg’s theory, not from the Dettol ad), this practice didn’t quite seem right when experiencing on Zomato’s Delivery orders.Solution: Have a time limit. If the feedback isn’t submitted by then, don’t ask. The time limit should depend on the impact of service. A holiday experience could have a month’s time limit but for a cab ride, probably not more than 24hrs.
Value of Individual feedback: If a person gives only between 3-5 stars everytime would you treat his 3 same as that of a person who only gives between 1-3 stars. If a feedback was given 1 year ago would it still be treated same as the one that was given yesterday? Zomato did a great job with this, described in detail on their blog.
Lately, Zomato has started treating delivery orders’ rating at par with dine-in’s rating. The basic problem with this treatment is that these 2 are very different services with food being the only common aspect out of 5. For dine-in, I would value service and ambience as well. Whereas for delivery, the packaging and delivery time would also be valued. Now by looking at a rating on Zomato it is difficult to say what this restaurant is good at. By design and the point mentioned earlier, a restaurant that does more delivery will continue to get better ratings.
Representation of feedback: How reviews and ratings are shown helps make best use of it. Showing who gave the rating (couple on honeymoon or solo traveller), when was it given, what was the rating specifically meant for (product or delivery) etc. helps comprehend better. It is also important to differentiate between what part of the feedback is for the service provider and what is for fellow users.
Should a transaction platform care about ratings and reviews? Ratings are an important aspect for curation. What comes on top of search and collection pages is determined by rating. A misinformed rating creates wrong expectation and that leads to a bad user experience. Remember, payments and delivery are a commodity, trust is the only differentiator.
Tripadvisor does a great job with reviews. Pretty detailed. Focus is on quality and not quantity.
Youtube used to have a 5 star ratings system. Now a binary system. Lesser cognitive load.
Flipkart web app used to ask ratings on past orders in a widget on the side bar, never forced over a pop-up.
Avoid using reviews system as a way to build content for SEO. A QnA section can do that job better.
SnapDeal, the ecommerce company, has a Sunshine Program to help Charitable Organisations. The program allows organisations to create their shopping list and publish on SnapDeal. SnapDeal promotes this amongst its users, who can order whatever they want to donate. SnapDeal delivers the products directly to the organisation.
Publishing wish-lists and gift registry for birthdays, weddings is popular in some cultures and countries. Letting charities do this brings in a lot of efficiency in the system, as only the most needed stuff is received as donation. And what better place to publish this than an ecommerce store? Users will be inspired to donate through this efficient as there is very little decision making to be done. Since these are usable products and not cash, there is more trust as well. All this while the store enjoys a positive brand recall. A true win-win-win.
The current state of the program is a great start and bringing bulk buy discounts, non-branded low cost products, donation receipts will make this a full fledged default destination for the privileged ones to give back.
When pricing a new product, understanding the tolerance level of the user is important. Knowing what is the maximum you can charge for a product without turning down your customers helps you maximize your revenue. This tolerance level theory applies to every feature optimization. The idea of exploiting tolerance level in product design is to move away from being a purist and keeping interactions clean to finding the right balance between clean product and clean product that makes money.
To be able exploit tolerance you need to understand what your true product is. Example – For most of India, a flight booking OTA’s true product may be booking the cheapest flight easily. Cheapest is the real product, easily might be exploitable for tolerance. A food delivery companies real product is food quality and delivery time, interface of app might be exploitable for tolerance.
Here are some examples that will help you understand what negotiables can be exploited for tolerance. Some product managers might want to call it a Growth Hack.
Way2SMS – A free SMS sending website. From the time of landing on homepage to sending the SMS, a user is shown about 15 ads. You might call it too much but if you understand the users’ profile you will be less worried about interface and more worried about delivery time of SMS. Way2SMS’s delivery time is under 2Seconds, even in peak hours.
Akosha – A freemium dispute resolution system for consumers. Akosha has pivoted to being Helpchat. Akosha used to send a notice to the disputing service provider on behalf of the consumer for free. If the dispute isn’t resolved, they charge the consumer Rs.500 to follow it up. I and friends have used Akosha thrice to solve disputes worth Rs.13K, Rs.30K, Rs.1K successfully. In all 3 cases Akosha did not charge, because the free service was good enough. Was there room to charge a fee/tip after the service? Absolutely.
GoZoomo: A friend used Gozoomo recently to buy a second hand car. They are doing a lot of offline work with the RTO for him, all for free. Charging for actual expenses borne on behalf of the consumer wouldn’t hurt.
Pinterest – If you land on Pinterest from Google, the first 2 folds are visible without login but when you scroll down further, you are asked to signup. Good balance of freemium.
Quora– Like Pinterest, Quora only allows you to read the answer that you directly landed on, everything else requires you to log in. Sometimes the user has no problem signing in, it’s just that you haven’t asked him well enough or you have given him a “Skip for now” button.
FindYogi – At FindYogi, we ask the user to login to see coupons applicable on a product. Most of our signups come from that 1 feature.
Coupon sites – They open the destination site before showing the actual coupon code. Does the user have a problem with that? Well, their growth doesn’t suggest that.
Insurance sites – Most of the sites ask you for contact details before showing a quote. If you are really serious about buying insurance, you may not mind it. Afterall, what’s the use of spending so much marketing money to bring the user on the site and not even creating a hook to contact them again.
GoDaddy – From the time of selecting the domain to buy to actually finalizing your order, they try to upsell you 3-4 products viz. SSL, Hosting, email, related domains. Does it hurt? Well what are the chances that he will bounce from step 2 and go to a competitor to buy a commodity product like a domain? Low revenues hurt more.
BigBasket – Untill recently, the earliest delivery slot that you would on BigBasket would be atleast 36hrs away. What really worked for them is the fullfillment rate. They were so good at getting what you ordered that they were ready bet on it with a 50% premium on refunds made for non-delivery. And when they promised a time-slot they really delivered then. Delivery slot is a negotiable, partial fulfillment or delay is not.
Not exploiting tolerance is like leaving money on the table. And once you know what the negotiables are, you will work harder to improve the non-negotiables. A lot of times maximizing the negotiable tolerance actually helps you discover a sustainable business model.
The important thing with tolerance level is that your margin in the tolerance exploitation is the opportunity for a new player to get it. BigBasket vs. Grofers is a good case here.
Back in 2005-06 the world had almost come to working with browser apps only. This was after we had started giving up on Yahoo chat as a desktop downloadable tool. Soon after mobile started picking up and WAP sites got popular. Later in 2007-08 iPhones were launched and all hell broke loose. Web developers now had to develop for environments that were different from the traditional web. Nokia’s symbian was still popular in developing economies. And then Android also caught up.
As if all the fragmentation wasn’t enough, browsers like Opera and UC web were running their own standards of HTML and no-JS sites. Google Chrome was lagging in mobile web story due to low bandwidth in developing economies so they started re-directing traffic through Google Web Light. They recently introduced AMP (Accelerated Mobile Pages) as a standard for content sites on low bandwidth. In a bid to reduce bandwidth overload for extended usage some developers took to Single Page Applications (SPAs) as well but that had it’s own challenge in terms of first time load and SEO.
With the whole fight around apps/no-apps, Google is now introducing app streaming for users with high-bandwidth access. So what does a developer do?
We tried to do a break down of all potential interfaces. Here’s what we got. Might be useful to think around this.
Web interface break down for India. (Click to expand)