“You can’t manage what you don’t measure.”

Deming and Drucker (2012, cited in McAfee & Brynjolfsson, 2012) explains why the recent explosion of digital data is so important. Simply put, because of big data, managers can measure, and hence know, radically more about their business, and directly translate that knowledge into improved decision making and performance. This forward thinking has caused business intelligence and big data analytics to become increasingly important in both the academic and the business communities over the past two decades (Chen at al, 2002). Industry studies have highlighted this significant development. For example, based on a survey of over 4,000 IT professionals from 93 countries and 25 industries, the IBM Tech Trends Report (2011) discovered business analytics was one of the four major technology trends this decade. Chief Economist at Google, Hal Varian (2012, cited in Chen et al, 2012) commented on the emergence of data analysis:

“So what’s getting ubiquitous and cheap? Data. And what is complementary to data? Analysis. So, my recommendation is to take lots of courses about how to manipulate and analyse data: databases, machine learning, econometrics, statistics, visualization, and so on.”

The previous research has largely focused on traffic driving activities and customer acquisition techniques such as online partnerships, social media influencers and email marketing. However, acquiring visitors is only the start of the process rather than, as many marketers believe, the end (Waisberg & Kaushik, 2009). Therefore, the attention now turns to data strategies, which closely supports content and engagement decisions and conversion strategies (Chaffey & Bosomworth, 2013).

The term ‘big data’ can take many forms such as messages, updates, images posted to social networks, GPS signals from mobiles, and many more. However, it is important for small businesses to narrow the scope and focus on an element of big data which is most important for their business. One important aspect and the focus of this research will include Web analytics. Web Analytics is the science and art of improving websites to increase their profitability by improving the customer’s website experience. It is a science because it uses statistics, data mining techniques, and a methodical process; it’s an art because the marketer must draw valuable and actionable insights to creatively improve the website (Waisberg & Kaushik, 2009). Asos are an excellent example of a retailer who have executed both the science and art of data analytics to top eConsultancy’s latest ‘Future of Retail’ benchmark report (Eccleston, 2016).

Asos topped the report for its impressive navigation performance on both desktop and mobile (Eccleston, 2016). Asos have not achieved this by chance, the navigation experience will be executed based on statistics and data mining techniques. Asos have a data driven culture and are known to test everything down to which models convert better in a specific item of clothing. While this may seem extremely confusing, difficult, time consuming and expensive for small businesses, it really isn’t!

The first important step is understanding web analytics is not a technology to produce reports; it is a process that proposes a virtuous cycle for website optimization (Waisberg & Kaushik, 2009). Within the process different methods and technology will be introduced to support each step of the process.

1. Define Goals

Each website owner should have a clear idea of what they are trying to achieve and define success according to their own objectives (Waisberg & Kaushik, 2009).

2. Build KPI’s

Key Performance Indicators (KPI’s) will show whether the objectives are being met. The Web Analytics Association (2007) agree of the three most important metrics – Unique Visitors, Visits/Sessions & Page Views. While these are the most common it is important to select the metrics which provide evidence your objectives are being achieved. Booth and Jansen (2009) identifies important KPI’s for each website type:

3. Collect Data

Once the company decides what it wants out of the Web analysis, it is time to find the right tool (Booth & Jansen, 2009).  For small businesses with smaller budgets than the likes of Asos, it is more appropriate and much simpler to use one of the most popular free analytics tools which is Google Analytics (https://analytics.google.com/) over paid tools which are analysed on the comparison site InfoWorld (http://www.infoworld.com/article/3128344/analytics/7-big-data-tools-to-ditch-in-2017.html). Google Analytics is a web based tool that generates detailed statistics and reports for the various KPI’s discussed above. Cordova-Ortiz & Jansen (2012) state Google Analytics is integrated into a site by a page tag; a snippet of JavaScript code, know as Google Analytics Tracking Code (GATC), which is embedded on every page of the website. Additionally, the analytics tool collects the referral information associated with the particular website this includes page visits directed from different websites such as online partnerships discussed in the last blog post. An example of the google analytics from this blog post can be seen below:

4. Analysing Data

Most Web Analytics efforts fail to catch on. This is because of the large volume of the data which is available and can often side track analysts to review data which is not in the businesses interests. As mention in the KPI’s section, Web analysts should push themselves to find the “critical few” important metrics for the site (Waisberg & Kaushik, 2009). Waisberg and Kaushik (2009) give questions ecommerce should ask to focus on the correct metrics:

• Visitors are coming to the website, but it having any impact on the site?
• If there is an impact on the bottom line, is the website converting enough?
• What’s selling and what is not? Why is it selling? How much of it?

5. Implement changes

As concluded by Phippen et al (2004) all the data gained is useless unless the data is understood and the findings are applied. The emphasis should be on Web intelligence – the information gleaned from a Website should be analysed and applied. A/B testing is a excellent method of implementing change derived from analysing data and comparing two versions of the implemented changes. This can include an update vs. the original page and then analysing the data again to see which page performed better. This video explains the A/B process:

The Benefits of analysing web analytics include:

One of the most important benefits includes learning information about the visitors to your website. This allows the business to make informed decisions and improvements based on their own consumers. In a survey of the state of business analytics by Bloomberg Businessweek (2011 cited in Chen et al, 2012), 97 % of companies with revenue exceeding $100 million were found to use some form of business analytics. Although this is focused on large businesses it shows the importance on understanding your data and the potential opportunities it provides.

However, there are some drawback:

Booth & Jansen (2009) advise allocating a full-time person in charge of the data once it is collected. This person should understand business needs, has knowledge of technology and marketing, has credibility and is already a company employee. Although it may be difficult and expensive to find for a small business, McFadden (2005) argues many experts agree that the return on revenue should be more than enough compensation.

Learning:

• “You can’t manage what you don’t measure.”
• Web analysis is not a technology it’s a ongoing strategic process.
• Although it seems like a complicated topic it can be simplified and specific to each individual business.
• Customer acquisition strategies is only the start of the process rather than, as many marketers believe, the end.

References

Booth, D. & Jansen, B. (2009) A Review of Methodologies for Analyzing Websites, IGI Global.

Chaffey, D. & Bosomworth, D. (2013) Digital marketing strategy: Planning Template. Smart Insights.

Chen, H., Chiang. R. & Storey, V. (2012) Business Intelligence and Analytics: From Big Data to Big Impact, MIS Quarterly. Vol 36, No. 4, pp. 1165-1188.

Cordova-Ortiz, A. & Jansen, B. (2012) Classifying Web Search Queries to Identify High Revenue Generating Customers, Journal of the American Society for Information Science and Technology. Vol 63, No. 7, pp. 1426-1441.

Eccleston, D. (2016) ‘What makes ASOS’s online customer experience so enjoyable? [Online] <https://econsultancy.com/blog/67823-what-makes-asos-s-online-customer-experience-so-enjoyable/> [Accessed 3^rd May 2017]

Econsultancy, 20^th May 2016 [Online] <https://econsultancy.com/blog/67823-what-makes-asos-s-online-customer-experience-so-enjoyable/> [Accessed 6^th May 2017]

IBM. (2011) The 2011 IBM Tech Trends Report. London: IBM.

McAfee, A. & Brynjolfsson, E. (2012) ‘Big Data: The Management Revolution’ Harvard Business Review, October 2012 [Online] <https://hbr.org/2012/10/big-data-the-management-revolution> [Accessed 5^th May 2017]

Phippen, A., Sheppard, L. & Furnell, S. (2004) A practical evaluation of web analytics, Internet Research, Vol. 14, No. 4, pp. 284-293.

Waisberg, D. & Kaushik, A. (2009) Web Analytics 2.0: Empowering Customer Centricity, The original Search Engine Marketing Journal. Vol. 2, No. 1, pp. 5-11.

Web Analytics Association (2007) Web Analytics Definitions. Washington: Web Analytics Association.

Online partnerships involve a smart collaboration of two or more organisations with the intent to develop a mid-term or long-term digital marketing program designed to meet each of their respective business goals (Kunitzky, 2009). Panico (2016) states interoranisational resource linkages can be an important source of competitive advantage, and on the basis of complementarities that might lead to value creation. This strategy is likened to a strategic alliance within the digital ecosystem. Singh (2016) believes digital partnerships are increasingly becoming commonplace because they are essential to create innovative or complementary products and services, and extend these offerings to reach broader audiences and markets.

According to Accenture’s digital collaboration index (2015), greater digital collaboration between G20 large companies and entrepreneurs could result in an additional £1.06 trillion in global economic output. One of these successful global digital partnerships include Apple and Nike. Nike CEO Mark Parker announced the relationship by stating “Nike is working with Apple on new software and experiences.” This includes new products such as Apple Watch Nike+.

Chaffey et al. (2009) identify online partnerships as part of a digital-communication tool for customer acquisition. He distinguishes different elements within online partnerships, such as: affiliate marketing, sponsorship, co-branding, link building and widget building. The remaining focus of this research will include affiliate marketing because it is growing in stature and highly regarded by key advertisers from large blue chip companies to SME’s (Tims, 2011). Smartinsights (2016) define affiliate marketing as the ultimate form of marketing communications since it’s a “pay-per-performance marketing” i.e. it’s a commission-based arrangement.

Chaffey (2016) states affiliate marketing partnerships within small businesses should include partnerships with other local businesses who aren’t in direct competition, or newspapers or local event guides. He further states, it’s really about thinking the type of content people are looking for and where it overlaps. A successful small business affiliate includes London on the Inside. They promote experiences, events, shopping, eating and drinking in London. This could be an interesting affiliate for local brands in London and follows Chaffey’s advice for small business affiliation strategy.

Singh (2016) identifies 7 steps when considering potential partnership opportunities:

1. Always lead with customer experience
2. Be open-minded and get creative
3. Set a clear strategy
4. Don’t be afraid to fail test
5. Look beyond your own back yard
6. Cultivating a digital culture starts at the top
7. Build a model for partnership that works for you

The benefits of this type of online partnership includes:

Affiliate marketing is especially beneficial to small businesses because they may struggle to maintain online partnerships which include multiple elements because of the investment and resources required to maintain relationships (Duke, 2016). Also, a successful affiliate-advertiser partnership has a potential win-win situation for both parties involved (Duffy, 2005) because the merchant or business selling products only pays when they make the sale or get a lead (smartinsights, 2016).

However, the drawbacks include:

A lack of knowledge because this is a fairly recent phenomenon and has no distinct offline parallel (Slack, 2013). Slack further explains that paid/display advertising is taking over from print advertising and how SEO spend compares to shop front real estate, but, affiliate marketing has no real direct offline comparison. Additionally, there is a shortage of academic studies and research surrounding the topic preventing practitioners learning the discipline. Unlike other areas of digital marketing research there is no template or recogniseable framework to support development of affiliate marketing in practice.

The learnings include:

Affiliate marketing is a technique used in customer acquisition strategies.

• Affiliate marketing includes a commission based arrangement. This can be extremely positive for small businesses because of the win-win arrangement with affiliates.
• Important to select the correct affiliates to prevent damaging your brand.
• There is a limited number of academic research within this digital marketing practice. It was difficult to identify helpful frameworks to support practitioners develop a correct approach to affiliate marketing.

As a result of a lack of academic research on this topic it is vital to gain insight from other individuals within the industry including affiliates blogs:

http://www.a4uforum.co.uk/

https://www.smartpassiveincome.com/

References

Panico, C. (2016) Strategic interaction in alliances. Strategic management journal.

Kunitzky, R. (2009) ‘What is partnership marketing?’ searchenginepeople, 29^th October 2009 [Online]  <http://www.searchenginepeople.com/blog/what-is-partnership-marketing.html> [Accessed 14 April 2017]

Singh, N. (2016) ‘The rise of digital partnerships: fad or way forward?’ The Telegraph, 5^th April 2016 [Online] <http://www.telegraph.co.uk/business/digital-leaders/horizons/2016-digital-partnerships/> [Accessed 13 April 2017]

Accenture (2015) Harnessing the Power of Entrepreneurs to Open Innovation. Turkey: Accenture

Chaffey, D., Ellis-Chadwick, F., Johnston, K., & Mayer. (2009) Internet Marketing: Strategy, development and practice. Harlow: Pearson.

Gurman, M. (2015) ‘Nike CEO discusses future of Apple partnership, exiting wearables, & Apple Watch’ 9TO5Mac, 8^th May 2015 [Online] <https://9to5mac.com/2015/05/08/nike-ceo-discusses-future-of-apple-partnership-apple-watch-exiting-wearables-video/> [Accessed 15 April 2017]

Tims, A. (2011) ‘Affiliate marketing: hard but lucrative’ The Guardian, 21^st May 2011 [Online] <https://www.theguardian.com/money/2011/may/21/affiliate-marketing-lucrative> [Accessed 13 April 2017]

Allen, R. (2016) ‘Affiliate marketing can be good for retailers, but ‘partner marketing’ is effective across all industry types’ Smartinsights, 2^nd September 2016 [Online] <http://www.smartinsights.com/affiliate-marketing/affiliate-marketing-strategy/dave-chaffey-talks-affiliate-marketing-grant-leboff/> [Accessed 10 April 2017]

Smartinsights (2016) ‘Affiliate marketing’ Smartinsights, 2016 [Online] <http://www.smartinsights.com/affiliate-marketing/> [Accessed 11 April 2017]

Duke, M. (2017) ‘Strategic partnerships & scalling – the magic formula’ The path forward, 2017 [Online] <https://thepathforward.io/strategic-partnerships-scaling-the-magic-formula/> [Accessed 12 April 2017]

Duffy, D.L., 2005. Affiliate marketing and its impact on e-commerce. Journal of Consumer Marketing, 22(3), pp.161-163.

Slack, A. (2013) ‘Affiliate marketing? It’s time for brands to learn the facts’ The Guardian, 25^th September 2013 [Online] <https://www.theguardian.com/media-network/media-network-blog/2013/sep/25/affiliate-marketing-brands-learn-facts> [Accessed 13 April 2017]

Social media is changing the business landscape and redefining how business communicate across their channels of distribution and with their customers (Rapp et al, 2013). Additionally, businesses are witnessing a new level of activism from an influential constituency rarely heard from in the past – ordinary consumers (Booth & Matic, 2011).

These ordinary consumers are known as social media influencers, they represent a new type of independent third party endorser who shape audience attitudes through blogs, tweets, and the use of social media (Freberg et al, 2011). Halzack (2016) claims this recent experimental marketing practice has morphed into a mini-economy with dizzying financial stakes. The social media analytics firm Captiv8 estimates that big brands are spending a collective $255 million per month for sponsored posts on Instagram alone with some influencers demanding more than $150,000 per sponsored post.

These social media influencers have the power to shape customer’s perception of a brand, this is particularly important for small businesses, as reputation is a crucial part of business enterprise risk management (Arnold, 2006). Booth and Matic (2011) state these storytellers must be leveraged and cultivated as part of a firm’s social media strategy. Recognising who your storytellers are and engaging them in your brand’s discussion can shape, or in some cases, protect a brands reputation.

Big brands such as ASOS and End Clothing already have strong networks of social influencers and adopted successful ‘word-of-mouth’ marketing techniques as part of their social media strategies. ASOS ‘insiders’ is an excellent example where social media influencers shape the brands online discussion.

The ‘insiders’ are a group of stylish men and women across the globe who are promoted on the ASOS website. The profiles on the website link to the ‘insiders’ social media accounts where they promote clothes, accessories and beauty products that are available to buy on ASOS.com.

Another great example is End Clothing’s consumer competitions to maximize their digital ‘word-of-mouth’ marketing. Anyone who purchases a product from end clothing enters the competition by sending an image of that purchase with #ENDelivered to be in with a chance of £100 gift voucher. This fantastic initiative reaches the influencers direct ‘friends’ and ‘followers’, but what makes them truly valuable is the number and relevance of their extended or indirect connections (Hall, 2010). This initiative remains authentic and targets normal consumers with rewards, however, as the influencer business grows, more people rush to join and the authenticity which made it so successful in the first place becomes questionable.

Booth & Matic (2011) have created a customisable social media valuation algorithm to support practitioner’s in the identification of influencers and streamline the analysis. The list of variables includes:

• Viewers per month (vpm). The number of visits to the blog per month.
• The popularity of blog post links inbound and outbound.
• Post frequency. Volume of posts per given time
• Media citation score. Volume and level of media that cites blogger.
• Industry score. Number of industry guru points based on industry events such as key notes, bylines and panel participation.
• Social aggregator rate. Level of participation in the social web (e.g. Twitter, Facebook and Instagram)
• Engagement index. Reader response and the quantity of comments.
• Subject/topic-related posts. Volume and immediacy of subject/topic-related posts.
• Qualitative subject/topic–related posts. Qualitative review of subject/topic-related posts.
• Index score. Identification and rank of influencer in the social web based on above variables.

Lessons learned:

• Important for small business to incorporate social influencers into their digital marketing strategy.
• Influencers provide a relatable and non-biased message which is vital for a brands reputation.
• ‘Word-of-mouth’ marketing through influencers is an important technique for social media follower acquisition.
• Crucial to carefully select each influencer, categorize them into specific tiers and build long lasting relationships which have a clear strategy.
• Remain authentic!

There are also many agencies that can support in this process of influencer identification including:

http://www.sociallypowerful.com/#influencer-marketing-agency

References

Arnold, M. (2006) CEO’s respect importance of reputation, Haymarket Media Inc: New York.

Booth, N. & Matic, J.A. (2011) Mapping and leveraging influencers in social media to shape corporate brand perceptions, Journal of Corporate Communications. Vol. 16, No. 3, p184-191.

Freberg, K., Graham, K., McGaughey, K. & Freberg, L. (2011) Who are the social media influencers? A study of public perceptions of personality, Public Relations Review. Vol. 37, No, 1, p90-92.

Hall, T. (2010) ’10 Essential Rules for Brand in Social Media’ AdvertisingAge, 22^nd March 2010 [Online] <http://adage.com/digitalnext/article?article_id=142907> [Accessed 26 February 2017]

Halzack, S. (2016) ‘Social media ‘influencers’: A marketing experiment grows into a mini-economy’ The Washington Post, 2^nd November 2016 [Online] <https://www.washingtonpost.com/business/economy/social-media-influencers-a-marketing-experiment-thats-metastasized-into-a-mini-economy/2016/11/02/bf14e23a-9c5d-11e6-9980-50913d68eacb_story.html?utm_term=.b670bc17e357> [accessed 27 February 2017]

Rapp, A., Beitelspacher, L.S., Grewal, D. & Hughes, D.E. (2012) Understanding social media effects across seller, retailers, and consumer interactions, Journal of the Academy of Marketing Science. Vol. 41, No. 5, p547-566.