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Social Influence Marketing: A guide to online marketing for start-ups and entrepreneurs
 

Social Influence Marketing: A guide to online marketing for start-ups and entrepreneurs

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This presentation describes our approach to online marketing for Hex Goods, an e-commerce retailer for designer goods. We designed a series of marketing campaigns using tools like Google AdWords, ...

This presentation describes our approach to online marketing for Hex Goods, an e-commerce retailer for designer goods. We designed a series of marketing campaigns using tools like Google AdWords, Facebook Ads, Twitter, affiliate programs, and blog campaigns. This presentation documents the approach, the results, and our learnings from the process.

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    Social Influence Marketing: A guide to online marketing for start-ups and entrepreneurs Social Influence Marketing: A guide to online marketing for start-ups and entrepreneurs Presentation Transcript

    • Our goal was to test the effectiveness of social media marketing tactics indriving value for an online retailer •  Based on cutting-edge research on the science of social networks, Social Influence Marketing aims to help companies use social influence The concept to spread messages through networks to drive product purchase or consideration •  A well-defined learning agenda will enable us to rapidly prototype, test, and iterate our service offering The goal •  We have a customer, Hex Goods, which will allow us to analyze marketing tests to determine the optimal channel, language, and tactics needed to drive desired behaviors •  Regular updates on test plan, execution, and learnings The output •  Final slide deck synthesizing our learning agenda, our findings, and ultimate recommendations | 1
    • The mystery-heuristic-algorithm framework guided our learning agenda •  Is social media an effective marketing Mystery channel? •  How do we identify influentials within a network? Heuristics •  How does a network’s structure affect our ability to spread a message? •  How do messages in a social network drive purchase or consideration within a Algorithm targeted demographic? | 2
    • Our customer: Hex Goods is an online boutique that features new and unique products from independent designers. Hex Goods launched in November 2011 with a collection of products for Christmas, followed by a Valetine’s Day collection in January/February 2012. By taking the concept of a small local design boutique and adding the elements of good online retailers (free shipping, a generous return policy, and a satisfaction guarantee), we hope to build a brand in a traditionally fragmented market. | 3
    • Social media is a great marketing tool if used effectively; however itrequires a real investment of time and energy to bear success Social media has Social proof and Network diversity is powerful targeting relevance are key to critical capabilities engage communities • Social media allows for • Startups are natural • Endorsement by n-th degree targeting echo-chambers community members lends social proof • Low barriers enable • Expand network diversity broad seeding of by: • Target based on messages o Adding team behavioral members with demographics, not just • Key is finding entry diverse networks traditional demographics points into relevant o Earning publicity networks for the target o Just ‘getting out • Communicate through market there’ appropriate social channels for maximum effectiveness | 4
    • Social media marketing manual for an entrepreneur1 Define the key metric or metrics that drive economic outcomes for your Define metrics business2 Create a network systems map to identify factors and loops that Build systems map positively and negatively influence key business metrics3 Target high-impact network variables, drivers, and feedback loops for Design testing marketing efforts campaigns4 Embed analytics to enable rapid learning from testing campaigns and Test, measure, and understand how marketing efforts are influencing the network system iterate | 5
    • 1 Establish proper metrics for the SIM campaign Example of metric selection process for our client Easy to Links to bus Useful for Driven by Potential measure goals small marketing Guidelines metrics samples Purchases 1.  Easy to measure 2.  Links to broader ü ü ü business goals in a Newsletter measurable way (eg, awareness, profit) sign-ups ü ü Referrals 3.  Useful with small sample sizes ü ü ü Return Visits 4.  Likely to be driven directly by marketing ü ü campaign Engaged Visits ü ü ü ü Visits ü ü ü ü | 6
    • 2 Create a network systems map to identify factors and loops that positively and negatively influence key business metrics Guidelines Examples from our map 1.  Develop systems map focused 1.  Focus on engaged visitors on optimizing your key metric 2.  Return visitors, newsletter sign- 2.  Determine the key secondary ups, purchases, attractiveness, metrics awareness, referrals, etc 3.  Determine other key variables 3.  Advertising, value proposition, that you can influence uniqueness, incentives, etc 4.  Determine the relationship 4.  Incentives drive referrals, between variables referrals drive publicity 5.  Identify the key feedback loops 5.  Engaged visitors-referrals- that exist awareness-new visitors- engaged visitors 6.  Identify among the loops, which has the greatest impact on the 6.  Referral loop, purchase loop, key metric incentive loop, etc | 7
    • 2 Example network systems map from our client Feedback Loops to focus on: •  Referral loop •  Investment loop •  Awareness loop •  Publicity loop Not focused on: •  Return loop | 8
    • 3 Design campaigns: Target high-impact network variables, drivers, and feedback loops for marketing efforts Guidelines 1.  Determine the top priority loops and drivers relevant to your key metric Our campaigns 2.  Determine the appropriate A •  Facebook campaign channels based on B •  Google AdWords •  Relevance C •  Blogs •  Budget constraints •  Twitter D •  Impact on systems map •  Referral program E 3.  Design pilot campaign 4.  Iterate campaigns based on results | 9
    • 4 Test measure iterate: Embed analytics to enable rapid learning from testing campaigns and understand how marketing efforts are influencing the network system Ideas  Learn  faster   Build  faster   Learn   Build  Split  tests   Focus  on  MVP  Customer  interviews   Outsource  Customer  development   Iteration  Root  cause  analysis   Free  &  open  source  software  Robust  advisory  board   Stage-­‐gates  Hypothesis  based  testing    Simulation  testing   Data   Develop               Measure  faster   Split  tests   Measure   Focus  on  analytics   Measure  what  matters   Real  time  analysis   Customer-­‐back  KPIs   Active  marketing   Tie  results  to  profitability   Quantify  results       Adapted  from  http://www.startuplessonslearned.com/  &  Eric  Ries  talks       | 10
    • 4 Example from Hex Goods •  Iteration: Tested four different marketing campaigns (AdWords, facebook1, facebook2, Z-ferral) Build faster •  Free & open-source software: Used Google Analytics to track visitor behavior; Venisim for network maps; Gephi & NodeXL for twitter analysis •  Measure what matters: Chose profitability-connected metrics from the onset •  Quantify results: Google Analytics allowed us to track connect source of visitor to site activity Measure •  Split tests: Horse-raced facebook campaigns to determine effectiveness •  Hypothesis-based testing: All testing campaigns were grounded in a detailed hypothesis about outcomes •  Simulation testing: Built robust network systems map to understand which Learn faster potential drivers could have the highest impact on our target metrics | 11
    • Campaign Details Feedback loops Description meant to drive Effectiveness Referral loop, A 3 targeted facebook ad Publicity loop, Facebook campaigns Awareness loop Investment loop B Google Campaigns focused on gifting Awareness loop AdWords and product-specific searches C Targeted design blogs to write Blogs Publicity Loop stories about Hex Goods D Targeted twitter analysis to Publicity Loop, Twitter determine optimum communities Awareness Loop, to follow and promote to Referral Loop E Developed affiliate program to Referral Loop, Referral Publicity Loop incentivize referrals | 12
    • Campaigns that were both relevant and had an element of“social proof” were most effective in driving engaged traffic Marketing ROI Cost per Bounce Cost per Source Campaign visitor ($) rate (%) engaged visitor Facebook Geography 1.60 83 9.42 Untargeted connections 0.45 83 2.65 Targeted connections 1.64 83 9.68 Wall posts 0.08 48 0.15 Blogs Oh, the Lovely Things 0.15 45 0.28 LA in the Bay 1.11 43 1.96 MBA Social 1.02 25 1.36 Nest Eagle Rock 0.45 36 0.71 Inventables 0.61 9 0.67 Google Headband 0.86 93 12.68 AdWords 0.38 93 5.66 Kindle Fire Zferral Affiliate program 1.79 60 4.46 | 13
    • A Facebook ads were one of the highest return options, but only when we used the social graphCampaigns Learnings ▪  Geography: Targeted standard ▪  Geography campaign performed Facebook ads to 10 zipcodes that poorly; click-through rates were low, represented our target market CPC was high, and the target population was very small ▪  Connections: “Sponsored stories” presented to people who ▪  Connections campaign performed very are friends with someone who well; most clicks and connections came “likes” Hex Goods from friends of friends ▪  Targeted connections: ▪  Targeted connections performed okay; “Sponsored stories” presented to limiting to target demographic put people who are friends with viewers outside of the friend circle someone who “likes” Hex Goods, and also falls in our target ▪  Facebook campaigns drive additional demographic value through “likes” that open up a marketing channel (wall posts are a very low cost channel) | 14
    • A Geography campaign results | 15
    • A Connections and targeted connections campaign results | 16
    • B Google AdWords performed poorly, and led to particularly high bounce rates, making them an expensive advertising optionCampaigns Learnings ▪  Gift campaign: Hex Goods ▪  CPC on Google AdWords is driven by general advertisement to people the competition; who else is bidding, searching for gift-related keywords and how much can they afford to pay? ▪  Product-specific campaigns: ▪  Winning on Google AdWords means Product-specific advertisements to having the highest customer LTV and people searching for keywords therefore the highest bid price related to those products ▪  Therefore, Google AdWords is an ineffective tool for cash-poor start-ups who don’t have customer histories and therefore little understanding of customer LTV ▪  In addition, bounce rates from Google AdWords are extremely high | 17
    • B AdWords campaign results | 18
    • C Blogs were an effective marketing campaign, especially when they were targeted to the right audienceCampaigns Learnings ▪  Oh, the Lovely Things: Featured ▪  Blogs and publicity outperform on a design blog that frequently advertising by a significant margin features products from Etsy designers ▪  Relevance is extremely important in driving traffic; design blogs dramatically ▪  LA in the Bay: Featured on a outperformed other blogs general women’s lifestyle blog from LA; contest offering a free ▪  Because the cost of publicity is mostly Hex Goods product time, blogs are a great resource for time-rich, cash-poor start-ups ▪  MBA Social: MBA lifestyle blog ▪  Nest Eagle Rock: Personal blog of one of my designers ▪  Inventables: Blog for a local Chicago start-up | 19
    • C Blog campaign results | 20
    • C Pinterest is a great way to be seen, but did not drive significant referral traffic 140 pins | 21
    • D A twitter network analysis is helpful in determining which users to invest in establishing relationships with Analyses Learnings ▪  Analyzed three key influentials ▪  Twitter analysis helps determine which on twitter with a direct reach of of the potentially influential users to over 920k design-interested target individuals ▪  Just counting followers is insufficient – followers must also ▪  Evaluated network structure to be a relevant demographic find brokers and ‘gate keepers’ that would impact target’s f-ratio* ▪  For targets with a very low f-ratio*, attempt to establish relationships with ▪  Assessed network makeup to its follows that have a high ratio better understand the ▪  A high ratio indicates that the communities our targeted individual is more likely to influential follows reciprocate your follow request*: F-ratio is a measure of “following-ratio” or ‘approachability’, defined as following relations divided by follower relationships | 22
    • D The importance of the f-ratioUnderstanding the f-ratio The f-ratio is defined as a twitter users number of following relationships divided by the number of follower relationships and is an estimate of a twitter users likelihood to reciprocally follow you. Furthermore, an f-ratio reveals the type of twitter user the individual is: •  A high f-ratio (1:many) indicates that the individual uses twitter to broadcast information, as such are very influential. These users tend to be celebrities, companies, and established brands. •  A low f-ratio (many:1) indicates that this user is primarily a consumer of information. Many individual, passive, and unengaged users fall into this category. •  A neutral f-ratio (1:1) indicates that this user may regularly engage in a dialogue with the community. These users are often respected bloggers, marketers, and smaller brands.Summary of our analysis Twitter user Description f-ratio Follower relevance @designmilk Popular modern design blog .0014 Low @thecoolhunter Trendspotting blog .003 Low @dwell Modern home goods and interior design .0018 High magazine and blog @dwell employees Employees of dwell corporation .34 High | 23
    • D designmilk’s relationships are primarily one-way and lie outside of our target demographic Interior design Companies & institutes # of followers: 470k f-ratio: .0014 Broad design, design blogs, product design | 24
    • D thecoolhunter’s had a diverse network and a high f-ratio; however, its network lacked communities of the target demographic Music Celebs & bloggers Style & fashion Ad & marketing agencies # of followers: 172k Architecture & design f-ratio: .003 News, travel, info | 25
    • D dwell’s network had a small communities of our target demographic and a large community of current and former dwell employees Blogs/websites Interior design Museums & institutes Employees Architecture # of followers: 355k f-ratio: .0018 | 26
    • D dwell’s employees represent an ideal entry point to dwell’s network; they were often re-tweeted by dwell and had an average f-ratio of .34:1 Employee community of dwell’s network | 27
    • E Referral program through Z-ferral was not as effective as we had hoped for driving incentivized referralsCampaigns Learnings Ambassador Program: •  Developed an incentivized referral ▪  Referral program needs significant program that required sign-ups by volume to find appropriate existing visitors ambassadors •  Utilized zferral embedded ▪  Rewards may need to be driven from software to award 10% “cash metrics other than purchases, reward” for any purchase driven especially in a start-up environment by referrals ▪  Referral needs marketing on its own. It Hello-bar: is not driven much by organic growth •  Implemented simple “hello bar” on the top of the site to inform visitors about the referral program Facebook mini-campaign •  Attempted to drive ambassadors based on personal facebook connections and hexgoods fans | 28
    • D How to incentivize sharing amongst groups? Why would people recommend? 1.  Available outlet (fbook, twitter, Guidelines for referral program gmail) 2.  Engage on this outlet 1.  Determine appropriate reward/ incentive system 3.  Satisfied customer, or •  Prizes interested customer •  Discounts •  Points 4.  Incentivized to share within •  Cash rewards the network 2.  Determine reward structure, 5.  Know someone who would like the product or service including whether to award for 2nd order referrals (eg, pyramid 6.  Think its relevant for your structure) community 3.  Choose appropriate program 7.  Think something is cool | 29
    • D We chose to use Zferral as our affiliate platform, but there are many options available Options for an affiliate program Our initial campaign choice Zferral •  Referral software, easy to integrate Campaign   1   2   3   4   with ecommerce sites 1st order 5%   10%   15%   10%   •  Based on a monthly subscription commission   plus 3% commission 2ND order 0   5%   0%   0%   •  Cash rewards and other options commission   available Buzz Referral •  Referral software •  Based on monthly subscription •  Referrals, social promo codes, and sweepstakes/contests NextBee •  Referral and customer loyalty program Vouchfor! Extole.com Qualityunit.com ReferralCandy | 30
    • D Example Referral Program page Hello Bar Landing Page Tracking page | 31
    • Executive Summary for Social Influence MarketingGoals:▪  Based on cutting-edge research done on the science of social networks, Social Influence Marketing (SIM) aims to help companies use social influence to spread messages through networks to drive product purchase or consideration▪  We have established a customer, Hex Goods, which allowed us to analyze marketing tests to determine the optimal channel, language, and tactics needed to drive desired behaviorsOutcome▪  The team ran 7 different marketing campaigns across 5 channels: Facebook, Google Adwords, Blogs, Twitter, and a referral program▪  Each marketing campaign was tracked for effectiveness and revised where necessary▪  The team determined three key takeaways from our work: –  Social media marketing channels have powerful targeting capabilities –  Network diversity is critical to spread messages, especially for a start-up –  Social proof and relevance are very important to engage the target audience and communityHandbook for Social Influence Marketing▪  The team recommends the approach to effectively run a social influence marketing campaign –  Define the key metric or metrics that drive economic outcomes for your business –  Create a network systems map to identify factors and loops that influence key metrics –  Design testing campaigns to target high-impact network variables, drivers, and feedbacks –  Test, measure and iterate using embedded analytics to enable rapid learning from testing campaigns and understand how marketing efforts are influencing the network system | 32