Category Archives: Insight

Understanding brand awareness, consideration and preference

Published / by Simon Foster

Brand awareness is vitally important in the marketing process. As consumers need to be aware of a product and brand to purchase it, then the more consumers who are aware, the more purchases take place. This hierarchical approach, begins with awareness and moves through consideration and preference to purchase.

This hierarchical path is sometimes called the sales funnel. Funnel metrics allow marketers to measure and control brand awareness, consideration and preference. These metrics allow marketers to say things like “We have 75% awareness and of those 35% would consider purchasing from us and 75% of the consider group place our brand in their preferred set.” Most marketers spend most of their time working to raise brand awareness, consideration and preference. Let’s explore brand awareness, consideration and preference one by one:

Brand awareness

Awareness is the number of people or percentage of a group that are aware of a brand. Awareness is measured in two ways, either as prompted or unprompted (spontaneous) awareness. Prompted awareness is measured by asking people if they are aware of the mentioned brand. It could be the brand name itself, a logo or the brand as part of a list of other brands. Unprompted or spontaneous awareness questions do not mention a brand name but asks consumers to name brands they are aware of in a given category. Examples would be “could you tell name ten airlines that you are aware of” or “can you name five soft drinks brands”.

Brand consideration

Consumers do not purchase all brands they are aware of. They purchase some but may actively avoid others. So, consideration examines whether consumers would consider purchasing a brand they are aware of.  Those who would consider purchasing a brand are measured as a subset of those aware of a brand. Here we see the hierarchical nature of the funnel in action; it is not possible to consider a brand you are not aware of. Consideration questions might ask “of the ten airline brands you are aware of, which would you consider using?”

Brand preference

Consumers tend to have a “preferred set” of brands – these are the set of brands within a category that they prefer to use. Going back to our hierarchical model, the preferred set can only come from within the considered set. Getting into the preferred set is the Holy Grail for many marketers but it’s not easy. Finding a place in the preferred set requires a contribution from all elements of the marketing process. A place in the preferred set is the result of many factors that can drive brand preference; a strong product developed through strong NPD, a product made available through good distribution,  a product pitched at the right price and a product back by good service.  You can see why advertising in itself cannot guarantee brand preference, but advertising can communicate a brand’s attributes which in turn can help to secure preference. Brand preference is measured by asking consumers which brands they prefer to purchase and use within a particular category.

How are these metrics measured?

Brand awareness, consideration and preference are attitudinal and exist within consumers’ minds. The only way they can be measured is through surveys which ask consumers about their relationship with brands.  These surveys can be collected though online panels, face to face or via phone research.

Proxy measures can also be used to build understating but theses are not a substitute for brand awareness research. Digital proxies include search traffic metrics which can be correlated to awareness and consideration. The important point with digital metrics is that they are behavioural, not attitudinal; they tell you that something is happening, but don’t explain why.

2017 UK Marketing Predictions

Published / by Simon Foster

Always fun to gaze into the year ahead.  Here are my predictions for 2017:

  • Mobile web use will be an increasing problem for Google: Mobile is now the dominant web use platform. In 2010 over 95% of web activity was delivered via PC, now it’s half that. As of this October, mobile had the edge with 51.3% of web traffic according to Stacounter. Why? Because domestic web consumption has shifted to mobile and particularly to tablets. PCs still dominate at work, but workplace constraints mean most consumer web traffic is generated in the evenings, not daytime. In the evenings, the dominant web platform is mobile not PCs. As we move further into a mobile platformed, high-utility ‘appworld’ the need for traditional PC-based search will decline.
  • More large-scale ad fraud will be exposed: This is going to become a much bigger issue because advertisers are going to divert more resources into actually finding it.  Just as doctors screening for a specific illness find more cases, so advertisers will begin to understand the true scale of online ad fraud. The recent Methbot scandal has revealed the scale of fraud that is now possible; c. $5m per day via 6,000 fake domains
  • TV will remain strong: TV’s ability to deliver mass impact, reach huge swathes of the population and drive high volume, low cost brand search traffic make it a powerful and important communications channel for marketers. Couple this with the relatively high trust scores attached to TV advertising and the growth of dual screening and you can see why TV will remain an important part of the marketing landscape in 2017.
  • There will be a bid for ITV: This has been a long time coming. My prediction is that this will happen in 2017. It might be from Google. Hold / Buy.
  • Campaign goes online only: Campaign, the UK’s ad industry weekly, will drop its print format and go online.  Many of Campaign’s Haymarket stablemates have dropped their print version. Campaign has only been able to hold out because all ad people over 40 like to see their faces in print.
  • Brexit currency changes: As the value of the Pound has slipped against the Dollar, Euro and Chinese Yuan we will see increases in the cost of imports. With an estimated £21bn food trade gap, increases in imported food costs will present significant challenges to FMCG marketers. However, export areas like tourism and specialist manufacturing will benefit.
  • Continued decline of newspapers: Continued big problems for newspapers. Goodness me, how their fortunes have changed.  As the ad market has grown, newspapers have continued to lose share. It’s no surprise as our appetite for real-time news puts next day reading into the dark ages.
  • EUDPR: Marketers and agencies will start thinking much harder about the new European Data Production Regulations due to come into force in May 2018. Under the new EU regulations the use of non-permissioned data and other breaches will attract fines of up to 4% of global turnover.  Ouch. That’s enough to make every CEO in Silicon Valley sit up and take notice.
  • Digital backlash: Out of all this we can see the seeds of a digital backlash. It’s been a great ride since Google launched in 1997, but twenty years on, there are some very big issues in digital; huge and endemic multi-million – correction, billion – dollar ad fraud, the rise of politically damaging fake news and the fact that only 50% of digital ads are ever seen by living, breathing, humans.  All this is enough to push many a marketing director back to the drawing board. Expect to see some interesting changes in spend patterns in 2017.
  • Direct mail could benefit from a digital backlash.  Direct Mail. Thought it was dead and buried? Think again.  A digital backlash is the perfect breeding ground for the resurgence of reliable, effective, accountable and physical media. Which channel ticks all four boxes? Direct mail. Add to this the fact that most Millennials have never received direct mail and you can sense a real opportunity.

Data planning and market research – mind the gap

Published / by Simon Foster

I once attended a research debrief to report the results of a survey into the communication effects of a direct mail campaign. The survey asked if the target group had received the direct mail piece and what they thought of it. The survey results were not good. According to the research, hardly any of the respondents could recall seeing the DM pack and even fewer claimed to have responded. There was disappointment; it was a big mailing and a strong offer, surely someone must have seen it and been motivated to respond. But all was not lost. In reality, away from the results of the survey, the campaign had in fact been very successful. I knew that the campaign was in the process of beating all its response, conversion and sign-up targets.  From a hard data point of view this campaign was on track to become one of the most successful DM campaigns ever run by the client.

So why was the recall in the research so low and the actual response so high? I can think of three explanations:

First, we were targeting a large group of the population. It was possible that even though the hard data results were good, we were drawing our DM response from portions of the population that simply hadn’t been included in the sample.   If we had a 25% response then that was a record-breaker from a DM planning point of view, but it still meant that the vast majority of the target – 75% – hadn’t responded. Those that had engaged with the mailing were far more likely to recall it than those who had not. So if our sample happened to comprise of 85% or 90% of those who did not responsd, then the recall results would be much lower than the response actually experienced.

The second explanation is more intriguing. Could it be that even though 1 in 4 of the target had responded, those that did respond had failed to make the connection between the what they’d actually done and what the research was asking them? In this scenario the sample is accurate and reaching our 1 in 4 respondents, but those who had responded forgot that they had done so when asked in research. Had they failed to connect the research question to the campaign and to their response behaviour?

The third explanation is that some of the respondents deliberately disconnected their actual behaviour from the answers they gave in the research. In other words, they did respond, but they didn’t want to say so.  They were using the research as a communication channel to share a point of view along the lines of ‘I’m not going to tell you exactly what I did. What I am going to tell you is that I didn’t like being perceived to be in your target audience, or perceived to be the sort of person who would buy the sort of product you were offering’.

Whatever the explanation, this taught me an important lesson; market research and behavioural data can say very different things. Asking people what they did, or think they did, can be very different to what they actually did. If market research tells you something, take it as an indicator not a fact. If it’s something big, do more digging around the research before you act on it.  But if hard data tells you something, whether it’s good or bad, whether you like it or not, you can be sure that it reflects changes in actual behaviour, the ultimate measure of marketing success or failure.

Marketing data analysis gets you closer to customers

Published / by Simon Foster

Smart data analysis can be a major source of campaign insight and even competitive advantage for brands and advertisers. The customer data owned by a brand advertiser can reveal

  • Exactly who buys a given product or service
  • Detailed information about the characteristics of those buyers
  • Which other products and services they buy
  • Which product and service offers they find most attractive
  • Which buyers buy more of certain types of products
  • How you can find more buyers with the same characteristics

These data analysis techniques can be applied to all types of customer data – whether it’s for a retail business, an online business or a call centre based business. Insight from data analysis can be applied across a wide spectrum; from adding inspiration to a creative brief through to changing a company’s entire business strategy.

You may think the claim that data analysis can change the destiny of a business is rather grandiose. But I can can think of two examples of breakthrough data insight from the same category that ended up contributing millions in additional brand revenues.

Sainsbury’s  – Sainsbury’s agency AMV were tasked with increasing the then ailing retailer’s sales by £2.5bn over a three year period. A seemingly impossible challenge until viewed as a data question. The AMV team calculated that £2.5bn equated to £833m per year which in turn equated to £16m per week.  It still looked like a big number until the AMV team considered that Sainsbury’s handled 14m customer transactions per week.  Then the target equated to just £1.14 per transaction. The brief to increase sales by £833m per week could be redefined as increasing each existing transaction by just £1.14. Now the target not only looked attainable, but this data insight led to the idea that lots of small changes could make a big difference.  From this insight came the campaign idea that consumers should “Try something new today”. By asking customers to ‘try something new’ they were able to persuade customers to spend at extra £1.14 every time they shopped.

Tesco – The Tesco Clubcard is now legendary as both a customer loyalty card and a source of information about customers.  Up until the introduction of the loyalty card, many retailers didn’t know who their customers were. And if they didn’t know who they were it was difficult for them to gather the data that allowed them to understand individual customers better. With the Club Card this all changed. Tesco were able to develop individual data driven relationships with their customers.  They were able to understand customer needs better and in doing so they gained competitive advantage over their rivals.