How to measure performance?

How would you rate this post? 1 Star2 Stars3 Stars4 Stars5 Stars (1 votes, average: 5.00 out of 5)
Loading...

 

Measurement for assessing the effectiveness of digital marketing should access the contribution of digital marketing at different levels:

  • Are corporate objectives defined in the digital marketing being met?
  • Are marketing objectives pans achieved?
  • Are marketing communications objectives achieved?

These measures can also be related to the different levels of marketing control specified by Kotler (1997). These include strategic control (question 1), profitability control (question 1), annual-plan control (question 2) and efficiency control (question 3).

Efficiency measures are more concerned with minimising the costs of online marketing, while maximising the returns for different areas of focus such as acquiring visitors to website, converting visitors to outcome or achieving repeat business.

Chaffey (2000) suggested that organisations define a measurement framework or create a management dashboard which defines grouping of specific metrics used to access digital marketing performance. He suggested that suitable measurement framework will fulfill these criteria:

  • Include macro-level effectiveness metrics which assess if strategic goals are achieved and indicate to what extent e-marketing contributes to the business (revenue contribution and return on investment). This criterion covers the different levels of marketing control specified by Kotler (1997), including strategic control, profitability control and annual plan control.
  • Include micro level metrics which assess the efficiency of e-marketing tactics and implementations.Wisner and Fawcett (1991) note that organisations typically use a hierarchy of measures and they should check that the lower-level measures support the macro-level strategic objectives. Such measures are often referred as performance drivers, since achieving targets for these measured will assist in achieving strategic objectives. Digital marketing performance drivers help optimise online marketing by attractive more site visitors and increasing conversion to desired marketing outcomes. These achieve the marketing efficiency control specified by Kotler (1997). The research by Agrawal et al. (2001), who assessed companies on metrics defined in three categories of attraction, conversion and retention as part of an e-performance scorecard, uses a combination of macro- and micro- level metrics.
  • Assess the impact of the e-marketing on the satisfaction, loyalty and contribution of key stakeholders (customers, investors, employees and partners) as suggested by Adams et al. (2000).
  • Enable comparison of performance of different digital channels with other channels as suggested by Friedman and Furey (1999).
  • The framework can be used to assess e-marketing performance against competitors’ or out-of-sector best practice.

When identifying metrics it is common practice to apply the widely used SMART mnemonic and it is also useful to consider three levels – business measures, marketing measures and specific digital marketing measures. The WebInsights diagnosis framework includes these key metrics:

  1. Business contribution: online revenue contribution (direct and indirect), category penetration, costs and profitability.
  2. Marketing outcomes: leads, sales, service contracts, conversion and retention efficiencies.
  3. Customer satisfaction: site usability, performance / availability, contact strategies. Opinions, attitudes and brand impact.
  4. Customer behavior (web analytics): profiles, customer orientation (segmentation), usability, clickstreams and site actions.
  5. Site promotion: attraction efficiency. Referrer efficiency, cost of acquisition and reach. Search engine visibility and link building. Email marketing. Integration.

This framework can be applied to a range of different companies. The groupings of measures remain relevant, although they are centred on sites or online presence, measures for engagement with social media should also be considered.

Channel promotion

These measures evaluate the volume, quality and value of where the website, social presence and mobile site visitors originate – online or offline, and what are the sites or offline media that promoted their visit. Web analytics can be used to assess which intermediary sites customers are referred from (the referrer) and which keywords they typed into search engines when trying to locate product information. Similar information on referrer is not typically available for visits to social media sites. Promotion is successful if traffic meets objectives of volume and quality. Quality will be determined by whether visitors are in the target market and have a propensity for the service offered (through reviewing conversion, bounce rates and cost of acquisition for different referrers).

Key measure

Referral mix. For each referral source such as paid search or display ads it should be possible to calculate:

  • Percentage of all referrers or sales (and influence in achieving sale last click or assist)
  • Cost per acquisition (CPA) or cost-per-cale (CPS)
  • Contribution to sales or other outcomes

Channel buyer behavior

Once customers have been attracted to the site we can monitor content assessed, when they visit and how long they stay, and whether this interaction with content leads to satisfactory marketing outcomes such as new leads or sales. If visitors are incentivised to register on-site it is possible to build up profiles of behaviour for different segments Segments can also be created according to visitors for whom cookies or login are used. Hurdle rates can be used to assess the activity levels for return visits e.g. 30% of customers return to use the online service within 90 days.

Key ratios

  • Bounce rates for different pages i.e. promotion of single page visits.
  • Home page views/all page views e.g. 20% = (2000/10,000).
  • Stickiness (how long a visitor stays on site) page views/visitor sessions e.g. 2 = 10,000/5000.
  • Repeats: visitor sessions/visitors e.g. 20% = 1000/5000.

Channel satisfaction

Customer satisfaction with the online experience is vital in achieving the desired channel outcomes. Online methods such as online questionnaires, focus groups and interviews can be used to access customers’ opinions of the website content and customer service and how it has affected overall perception of brand. Benchmarking services such as Foresee (foreseeeresults.com) based on the American Customer Satisfaction Index methodoloy are published for some industries. These assess scrores based on the gaps between expectations and actual service.

Key measure
Customer satisfaction indices. These include ease of use, site availability and performance, and email response. To compare satisfaction with other sites, benchmarking services can be used.

Channel outcomes

Traditional marketing objectives such as number of sales, number of leads, conversion rates and targets for customer acquisition and retention should be set and then compared to other channels. Dell Computer (dell.com) records on-site sales and also orders generated as a result of site visits, but placed by phone. This is achieved by monitoring calls to a specific phone number unique to site. Key marketing outcomes include:

  • Registration to site of subscription to an email newsletter
  • Requests for further information such as a brochure or a request for a call-back from a customer service representative
  • Responding to promotion such as an online competition
  • An offline (phone or store) lead or sale influenced by a visit to the site
  • A sale on-site

Key measure

  • Channel contribution (direct and indirect).

A widely used method of assessing channel outcomes is to review the conversion rate which gives an indication of the percentage of site visitors who take a particular outcome for example:

  • Conversion rate, visitor to purchase = 2% (10,000 visitors of which 200 make purchases).
  • Conversion rate, visitors to registration = 5% (10,000 visitors of which 500 register).

A related concept is the attrition rate which describes how many visitors are lost at each step of a conversion funnel from landing page to checkout. A key feature of e-commerce sites is that there is a high attrition rate between a customer adding an item to a basket and subsequently making a purchase. It surmised that this is due to fears about credit card security, and that customers are merely experimenting. Potential reasons for causing attrition on an e-commerce site:

Acquisition

  • Wrong audience
  • Unclear marketing message
  • Slow page load

First impressions

  • Unengaging look and feel
  • Clumsy site navigation
  • No real-time stock information

Product selection

  • Awkward selection
  • Price uncompetitive
  • High shipping cost

Payment and fulfillment

  • Card validation error
  • No email notification
  • Failed delivery

Channel profitability

A contribution to business profitability is always the ultimate aim of e-commerce. To assess this, leading companies set an internet contribution target of achieving a certain proportion of sales via the channel. Assessing the contribution is more difficult for a company that cannot sell products online, but the role of the internet in influencing leads and purchase should be assessed. Discounted cash flow techniques are used to assess the rate of return over time.

Multichannel evaluation

The frameworks we have presented are explained in the context of individual channel, but with the contribution of the channel highlighted as percentage sales or profitability. Wilson (2008) points out, there is a need to evaluate how different channels support each other. He says:

Traditional metrics have been aligned to channels, measuring resources input or leads in at one end and the value of sales generated by the channel at the other end. For companies that have been operating in a single channel environment, this might have been relatively efficient – but it no longer works when the organisation diversifies to a multichannel approach.

He suggests the most important aspect of multichannel measurement is to measure ‘channel cross-over effects’. This involves asking, for example: ‘How can the impact of a paid search campaign be measured if it is as likely to generate traffic to a store, salesforce or call centre as to a website?’ and ‘How can the impact of a direct mail campaign be tracked if it generates website traffic as well as direct responses?’

See an example of a balanced scorecard style dashboard developed to assess and compare channel performance for retailer. Results:

Revenue

  • Multichannel contribution
  • Degree multichannel set up
  • Costs per channel
  • Degree of sweating assets
  • Multichannel infrastructure costs

Core processes

  • Productive multichannel usage
  • Price (relatively to competitors / other channels)
  • Quantity of integrated customer view

Customer and stakeholders

  • Overall customer satisfaction
  • Customer propensity to defect
  • Customer propensity to purchase
  • Customer perception of added value
  • Integration of customer experience

People and knowledge

  • Staff satisfaction
  • Appropriate behaviours ‘Living the brand’
  • Willingness to diversify / extend the brand
  • Knowledge to target customer

Chaffey, D. and Ellis-Chadwick, F., 2012. Digital marketing: strategy, implementation and practice (Vol. 5). Harlow: Pearson.

Related posts