Share of Heart, Share of Mind Flashcards
Share of heart and mind metrics purpose
To diagnose market results (aka market share type metrics) by understanding consumer cognitions, emotions and behavioural intention.
Hierarchy of effects
Hierarchy of effects states that consumer cognitions, emotions & behaviour can be arranged in a linear sequence.
Each step needs to happen before the one before it (hence the term hierarchy)
Hierarchy of Effects expressed through
- AIDA: attention à interest à desire à action (sales model from early 1900s)
- DAGMAR (Defining Advertising Goals for Measured Advertising Results, 1960s): awareness à conviction à comprehension à action
- Not all situations follow the same “Learn® Feel® Do” model (such as AIDA) - as a result objective setting becomes unreliable. A better strategic tool: the FCB-grid.
Tracking studies
- The most typical source is “brand tracking study” – a survey that is collected among the target group over time (hence the name tracking).
- Can be continuous, wave tracking, combination, online or in person, for a general purpose, to track effectiveness of advertising and general brand health
Purchase funnel
Pre awareness Awareness Research and familiarity Opinion and short list Consideration Purchase Brand ambassador/ saboteur Repurchase intent - purchase intent trigger or defection
Awareness
the percentage of potential customers or consumers who recognise or name – a given brand. Marketers may research brand recognition on an “aided” or “prompted” level. Alternatively, they may measure unaided or unprompted awareness.
Top of mind
the first brand that comes to mind when a customer is asked an unprompted question about a category. The percentage of customers for whom a given brand is top of mind can be measured.
Ad Awareness
the percentage of target consumers or accounts who demonstrate awareness (aided or unaided) of a brand’s advertising. This metric can be campaign – or media specific, or it can cover all advertising.
Brand/ Product knowledge
the percentage of surveyed customers who demonstrate specific knowledge or beliefs about a brand/product.
Brand awareness
measures to what extent the brand/company is present in consumers’ memory:
- Unaided: only count the first mentions
- Aided: count the number of mentions of each brand and divide by the total number of respondents.
Brand Attitudes
- Purpose to assess deep-seated beliefs, thoughts, feelings about a brand
- Built on the general psychological concept of attitudes
- Family of metrics, not a single one!
- Relatively stable, positive or negative assessments of an object (in our case, brand or company)
- Can be cognitively (rational attitudes, beliefs, knowledge) or emotionally based (feelings, emotions)
- Attitudinal loyalty (how much consumers are committed to a brand) is also measured
Key metrics for attitudes
- Attitudes towards a brand/product: this brand is for people like me
- Perceived value for money: this brand usually represents a good value for money
- Perceived quality: compare with other similar products/ brands
- Intentions: customers stated willingness to behave in a certain way
- Purchase intentions: customers stated purchase intentions
Brand Attitudes Diagnostics
- Detailed metrics about consumers’ beliefs about particular aspects of the brand/product
- Usually a “battery” of questions respondents need to assess, not a single-item measure
- Has to relate to strategic issues
- Can be functional features (performance, quality, specific benefits).
- Can be emotional characteristics (emotions associated with the brand, brand personality measures).
Purchase Intention
- willingness to buy in the future.
- purpose: to assess how much respondents are willing to buy
- Theoretical support: purchase intentions are well correlated with actions. Theory of Reasoned Action, Theory of Planned Behaviour
- Assesses behaviours on a self-report basis
Share of heart and mind metrics challenge
- Cross check self-report tracking data with other sources (sales, distribution channel data, etc.)
- Use benchmarks
- Separate customer from non-customer segments
- Cut data by users/nonusers, important segments
- Be aware of methodological changes, external (non-marketing) events that can bias the results, “break” trends