iod sales and marketing forum 8oct13

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Marketing and data Analytics – How small and medium enterprises can benefit from Big Data,

Marketing and Social Media analytics and good, old school, statistics

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Introductions

• I am ________ and my company does _________

• With regards to data and analytics1. The board of Directors is sensible to their

value and we have a strategy in place.

2. We have data in our company.

3. What data?

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What are we going to talk about?

• Big data• Analytics and analysis gap• Social media analytics (Twitter)

(unstructured data)• Business analytics (structured data)

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A Google search…

Keywords # of Hits

Big data 2bn

Big data analytics 98m

Social media 2.8bn

Social media analytics 132m

Marketing 1.67bn

Marketing data 1bn

Marketing data analytics 60m

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What is Data?

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Data …

• The result of observations (how many road accidents on the M27, how many people report to A&E in a day, how tall are the members of IoD, how many positive tweets are received in one day)

• Primary first hand experience

• Secondary data collected by somebody else

• Structured they can be organised in structures (databases) based on specific methodology (numbers, words)

• Unstructured text, images, sounds, videos

• Data become information after they are analysed and provided with sense

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Why do we need data?

• Every single business objective is measurable

• Nobody has unlimited resources, hence everybody needs strategies

• How do we select strategies and measure progress? By comparing models based on numbers and by collecting and analysing data

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What is Big Data

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Big Data

Big data describes a massive volume of both structured and unstructured  data that is so large that it's difficult to process using traditional database and software techniques.

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Big Data

The term may seem to reference the volume of data, but it may refer to the technology (which includes tools and processes) that an organization requires to handle the large amounts of data and storage facilities.

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Big Data

The 3V

Volume

Velocity

Variety

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How are Big Data generated?

Nectar Cards 19,000,000 24 swipes every second everyday

Tesco Clubcard 16,000,000

Credit Cards 63,000,000

Debit cards 88,000,000 10.3 bn yearly transactions, £502 bn

Mobile

subscriptions

82,700,000

Home broadband 21,700,000 55% of adults have a social media

profile

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Big Data

• Employees generating data

• Users generating data

• Machines generating data

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Cloud event

BusinessTransactions

Operationaldata

Complex eventprocessing

Business processing& activity monitoring

Data integration& management

Stream eventanalytics

Process eventanalytics

Datawarehouse

Sub-secondlatency

Minuteslatency

Hours/dayslatency

Dataanalytics

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The analysis gap

Analysisgap

• Algorithms• Database• Parallel processing

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Supercomputing

Parallelcomputing

Server/cloudcomputing

Desktop

Spreadsheet

Statistical packages

Business Analytics packages

Purpose designed packages

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SW # of rows # of columns Memory Other Cost

Google Docs 256 20MB 400,000 cells40,000 formula cells200 sheets per workbook

Free

Excel 2003 (32-bit) 65,536 256 2.1 GB 16,777,216 cells £150+

Minitab 10,000,000 4,000 System Hardware and OS150,000,000 cells

£1,200/y

STATA System System System 2bn cells £4,000/y

R System System System 3bn+ cells (128TB on a Linux 64-bit system) Free

SPSS System System System 100,000 rows on display £2,000+/y

SAS System System System BI solution £4,000+/y

Fortran System System System System (Mainframes and supercomputers) A few £k

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Supercomputing

Parallelcomputing

Server/cloudcomputing

Desktop

Spreadsheet

Statistical packages

Business Analytics packages

Purpose designed packages

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System cost vs System complexity

SystemHardwareSoftwareStructureUtilitiesHR

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Why do we need analytics

Because we need to gain insights and act on complex issues

Analytics allow thinking, trending and

what-iffing

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Smart analytics

• Advanced statistics• Predictive modeling and analytics• Web event analytics• Text and social media analytics• Social networking analysis (influencers,

opinions)

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Social media analytics

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Social media sample goals

1. Increase inbound leads at a low cost

2. Expand reach of thought content

3. Engage and excite influencers

4. Better understand, identify and engage potential buyers

5. Improve customer service and satisfaction

6. Enhance outbound campaign program effectiveness

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Social media tactical plan

1. Blog (Wordpress, Blogger, Tumblr, Typepad, Blog.com)

2. Social networks (Facebook, Linkedin, Pinterest, Google+)

3. Microblogging (Twitter/Vine)

4. Social PR (Bloggers)

5. Widgets

6. Bookmarking / Tagging (Reddit, Digg, Stumbleupon; Zite, Flipboard)

7. Blog commenting / Q&A sites (TripAdvisor)

8. Online video (YouTube, Vimeo, 70+)

9. Photo sharing (Flickr, Photobucket, Pinterest, 30+)

10. Podcasting

11. Presentation sharing (SlideShare, Scribd, 30+)

12. Other: Wikipedia, RSS (Feedly), Wikis (80+)

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Blog

Short term objectives1. Increase recognition

– X number of posts– Blog publication schedule– RSS/Social share button

2. Increase engagement– Encourage comments– Interact with active

readers (they are all potential advocates)

Metrics1. Number of posts2. Number of social shares3. Audience growth4. Conversation rate5. Conversions6. Subscribers7. Inbound links8. Directory listing

(Tecnorati, Alltop)9. SEO improvements

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Twitter

Short term objectives1. Promote content through

Twitter2. Segment influencers and

create lists3. Utilise promoted Tweets4. Communicate support

issues from Twitter to support team and ensure follow-up

5. Listen to relevant conversations

6. Build reputation

Metrics1. Followers2. Mentions3. Retweets4. Retweets reach5. Replies reach6. Number of lists7. Social capital (influence

of twitter followers)8. Number of potential

prospects sent to sales9. Posts

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Social Marketing Analytics

Business Objectives

KPI

Foster DialogueShare of Voice, Audience engagement, Conversation

Reach

Promote Advocacy Active Advocates, Advocate Influence, Advocacy Impact

Facilitate Support Resolution Rate, Resolution Time, Satisfaction Score

Spur Innovation Topic Trends, Sentiment Ratio, Idea Impact

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Foster Dialogue

sMentionsCompetitoronsBrandMentionsBrandMenticeShareOfVoi +=

TotalViewsTrackbacksSharesCommentsgagementAudienceEn ++=

enceExposurTotalAudietingeParticipaTotalPeoplonReachConversati =

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Promote Advocacy

atesTotalAdvocst30days)vocates(laofActiveAd#catesActiveAdvo =

ceateInfluenTotalAdvocsInfluencecate'UniqueAdvofluenceAdvocateIn =

yTrafficeOfAdvocacTotalVolumonenConversivocacyDrivNumberOfAdpactAdvocacyIm =

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Facilitate Support

iceIssuesTotal#ServactorilylvedSatisfIssuesResoTotal#utionRateIssueResol =

esiceInquiriTotal#ServTimeryResponseTotalInquiTimeResolution =

rFeedbackAllCustomen)C,B,utA,edback(inpCustomerFeonScoreSatisfacti =

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Facilitate Support

ntionsAllTopicMeionscTopicMent#OfSpecifisTopicTrend =

ntionsAllBrandMesandMentionNegativeBr:Neutral:PositiveatioSentimentR =

MentionsShares,n,onversatioTotalIdeaCMentionsShares,ons,ConversatiofPositive#IdeaImpact =

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# of followersNatwest_help 23kBrand Republic 150kThe Wall UK 15kTwitter Ads UK 14k

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Daniel has 15,600followers

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The Critical Couplehas 11k followers anda blog

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Marketing Weekhas 90k followers

The Drumhas 72k followers

Michael Vaughanhas 460k followers

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Business analytics

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mk

nxmk

0x

kxy

nmxy

−=⇒>

>=

+=

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Variable + Fixed CostsSales Revenues

Breakeven point

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0x

ey

x8y410x

7

>=

=−

−

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Infant Failure RateMaturity Failure RateObserved Failure rate

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Year Sales CAGR YoY Av sell

2011 1,000,000 1,000

2012 1,249,000 25% 1,249

2013 1,499,000 14.5% 20% 1,498

2014 1,707,151 14%

Sales 2011/13 and forecast 2014

£0

£200,000

£400,000

£600,000

£800,000

£1,000,000

£1,200,000

£1,400,000

£1,600,000

£1,800,000

2011 2012 2013 2014

Years

GBP

Sales

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Sales analytics

Year # of customers Sales Mean sale Median sale

2011 1000 1,000,000 1,000 1,000

2012 1000 1,249,000 1,249 1,000

2013 1000 1,499,000 1,498 1,000

The above results are achievable by having, in 2012,999 customers spending £1,000 and 1 customer spending 250,000 and, in 2013,998 customers spending 1,000 and 2 customers spending 250,000 each.

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Average price of a pint of Lager in 290 locations

Loc Pri Loc Pri Loc Pri Loc Pri Loc Pri Loc Pri Loc Pri Loc Pri Loc Pri Loc Pri Loc Pri Loc Pri1 3.00 51 3.35 101 3.00 151 2.34 201 4.00 251 2.94 26 3.90 76 2.85 126 2.80 176 3.90 226 2.50 276 4.402 4.20 52 3.05 102 3.00 152 2.55 202 3.10 252 2.90 27 2.60 77 3.00 127 2.40 177 2.00 227 3.20 277 2.903 2.30 53 3.50 103 2.85 153 2.40 203 3.00 253 3.10 28 3.00 78 2.50 128 3.30 178 1.59 228 2.70 278 3.254 3.00 54 3.20 104 3.55 154 3.05 204 3.25 254 3.00 29 3.00 79 2.50 129 2.60 179 2.75 229 2.90 279 2.405 1.62 55 2.20 105 3.10 155 2.89 205 0.25 255 2.85 30 3.00 80 4.20 130 3.95 180 3.25 230 2.65 280 2.456 2.75 56 2.50 106 2.00 156 2.70 206 4.00 256 3.50 31 2.80 81 3.85 131 3.25 181 3.10 231 2.20 281 2.957 3.50 57 0.99 107 3.00 157 2.58 207 3.00 257 2.50 32 3.20 82 2.70 132 4.50 182 4.50 232 2.90 282 4.008 2.92 58 4.50 108 3.20 158 4.30 208 3.00 258 3.25 33 2.85 83 3.90 133 3.80 183 2.60 233 2.02 283 2.559 2.78 59 2.60 109 3.20 159 2.90 209 4.20 259 2.80 34 2.77 84 2.10 134 3.20 184 2.80 234 2.90 284 2.65

10 2.85 60 2.40 110 3.00 160 3.60 210 2.10 260 1.60 35 2.85 85 2.95 135 3.50 185 2.00 235 2.30 285 2.4011 2.70 61 3.50 111 3.85 161 2.95 211 2.22 261 1.76 36 1.95 86 3.10 136 2.37 186 3.15 236 2.50 286 3.0012 3.00 62 3.50 112 4.40 162 3.00 212 3.30 262 1.95 37 2.58 87 2.87 137 1.99 187 3.00 237 3.30 287 3.3013 3.60 63 3.00 113 2.50 163 2.50 213 2.30 263 2.60 38 3.08 88 2.50 138 3.30 188 2.95 238 2.60 288 3.0014 3.64 64 3.40 114 2.90 164 2.30 214 2.72 264 2.00 39 2.36 89 3.60 139 3.55 189 3.00 239 1.46 289 3.2015 3.20 65 3.22 115 1.80 165 3.00 215 2.90 265 3.40 40 3.70 90 3.50 140 2.52 190 2.65 240 4.80 290 4.2516 3.30 66 3.80 116 2.78 166 3.80 216 3.20 266 3.00 41 2.60 91 2.52 141 2.30 191 2.50 241 3.3017 1.75 67 2.75 117 2.35 167 2.10 217 3.20 267 3.20 42 2.85 92 2.60 142 2.20 192 3.00 242 3.5018 2.45 68 2.50 118 3.00 168 1.95 218 4.30 268 2.50 43 2.90 93 3.14 143 2.60 193 2.50 243 3.4019 3.25 69 3.10 119 2.90 169 3.15 219 3.60 269 1.90 44 2.72 94 2.45 144 3.50 194 3.00 244 2.9020 2.34 70 3.00 120 3.00 170 2.50 220 2.40 270 2.88 45 3.60 95 3.20 145 2.80 195 2.01 245 2.8521 3.50 71 2.85 121 2.60 171 3.05 221 3.00 271 2.60 46 1.00 96 3.38 146 4.10 196 4.50 246 1.8622 2.96 72 3.40 122 3.25 172 2.95 222 2.90 272 3.50 47 1.99 97 2.40 147 4.20 197 2.75 247 2.4023 3.30 73 2.85 123 2.30 173 2.90 223 2.90 273 3.30 48 2.80 98 2.55 148 3.00 198 2.60 248 3.0624 3.10 74 4.90 124 6.00 174 2.50 224 2.60 274 5.90 49 3.40 99 2.80 149 3.33 199 2.35 249 3.2525 2.00 75 2.50 125 4.00 175 1.75 225 2.95 275 2.90 50 2.90 100 3.40 150 3.30 200 1.90 250 2.50

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Average Price of a Pint of Lager in 290 locations

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1

2

3

4

5

6

7

1 14 27 40 53 66 79 92 105 118 131 144 157 170 183 196 209 222 235 248 261 274 287

price

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VariableCoun

tMean StDev Minimum Median Maximum Mode

N for mode

Skeweness Kurtosis

Pint 290 2.94 0.69 0.25 2.91 6.0 3 30 0.51 2.89

6.005.254.503.753.002.251.500.75

70

60

50

40

30

20

10

0

Pint

Freq

uenc

y

Histogram of PintNormal

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Conclusions

It is possible to observe everything

It is possible to collect and analyse data in high volumes, variety and velocity

Companies must equip themselves with adequate resources and tools (people and systems)

Do not underestimate the weaknesses of Excel

Do not underestimate the value of employing a Data Analyst/Scientist alongside your Marketing Manager

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Conclusions

The most valuable intangible asset of a company is the insight of their target market

Given the technology and the knowledge available, there is no excuse for not having insight of a target market