The Anatomy of a Brand Purchase – Part 2

We started with the question

What kind of relationship do customers want to have with your brand?

on the path to better understanding and engaging profitable customers by coming to communicate with them in their own language – one of four (Wallet, Mind, Heart, Life) reflective of the way in which they come to value your brand.

In this section we put forth a new tool, Marketing Interaction Impact (MII) to help manage those relationships and successfully trigger brand purchases.

Marketing Interaction Impact:

The Marketing Interaction Impact (MII) tool focuses on tracking the interactions and channels that are to be part of an event campaign designed to help the customer progress toward the final act of purchase. In other words, if the purchase is the applause of our customers, then the purchase stream is the concert. (with all due deference to Ken Blanchard)

This is more than a traditional integrated marketing program or media neutral planning in that we engage a much wider scope of touch points.

Managing the purchase stream requires the ability to sequence, implement and monitor brand impact tasks.

There are 3 basic types of brand impact task events.

I. Communication Events

a. Information – a (partial) telling of the brand story

b. Interaction – a consumer initiated, program constrained exchange

c. Dialogue – a two-way dynamic flow of information (Between the customer and brand or between the customer and community)

II. Experience Events

a. In store

b. Web store

c. Call centre

d. Product

e.Public setting

III. Overture Events

a. Messaging – one way offer-to-purchase

b. Negotiation – two way offer-to-purchase

In isolation each of these tasks may be sufficient to spark a brand purchase, however having all three work in concert increases the likelihood of brand transactions. And like a tripod, an imbalance between the three will result in a less stable brand.

MII seeks to consider the brand impact task, channel touch points and ‘language’ of the conversation between the brand and customer with the goal of finding and engaging in the most efficient spectrum of events that will impact the customer resulting in a purchase. The customer’s touchpoints are evaluated for their cost efficient ability to support a brand transaction.

By contrast the Marketing Contact Audit model (MCA – See Appendix A) derives a single blended (rational, emotional, credible) category score reflecting the media channel’s ‘potency’ (CCF) and then “measures the consumers’ perception or memory of having encountered a specific brand via a particular contact” (BEP). A tool they describe as empowering brand owners/marketers to (1) identify and select the critical contacts that are relevant for a particular brand, (2) integrate across these key contact points, and (3) deliver brand experience through a relevant and pertinent set of consumer brand encounters at a minimum cost, but with maximal impact.

MII is based on a different premise, that the brand customer’s perspective of the brand (not the category) is paramount. At its core is a belief that valued customers:

1: need and want to connect in different ways with the brand as they move toward the purchase tipping point

2: will be more receptive to messages expressed in their language (W, M, H, L)

3: will be more sensitive to different elements in the brand value chain as communicated/messaged to them

By tracking the brand activity within the relevant profitable customer segments you will be able to look at the timeline of intervening events leading up to the purchase and with more data points, come to understand various effective sequences your customer segments respond to leading to a more optimal balance between push and pull marketing.
Putting it all together yields a simple equation:
Purchase (P) = xC + yE + zO = 1

where:

C = Communication events

E = Experience events

O = Overture events

with x,y,z being the derived impact weighting contribution of the purchase event stream

Consider the following scenario (Table 1) where a customer came to intersect with:

C: 10 brand communication events (2 print ads, 3 banner ads, 2 flyers, 2 website visits, 1 email to the help desk)

E: 3 experience events (2 visits to the web store, 1 visit to the store)

O: 2 overture events (2 email offers)

before making the ultimate purchase in store.

That sequence of events would yield the following customer formula/response model (see Table 1 for calculation):

10.7%C + 35.7%E + 53.6%O = Purchase = 1

which tells us the purchase stream appears to have been strongly (54%) but not exclusively impacted by purchase offers, that experience and communication events (in this example) had a 46% correlational/supportive contribution in that time frame. (Note: We are counting event impressions in order to keep things on a common basis. With costing data one achieves an ROI model.)

We can debate whether the purchase would happen regardless as a result of self-recognized need, or that relying on purchase offers alone to support the brand leads to the creation of a transactional brand – the point remains these events intersected with the customer and had some impact. And based on this result (subject to comparison with other relevant customer results) it provides direction in defining the components and levels of support for a more balanced brand that yields a cost effective purchase stream. Naturally over time, experimentation and analysis will lead to greater clarification.

To more completely model the real world, the formula would need to consider several additional factors:

1. less frequent events in the purchase triggering stream are likely more powerful than more frequent events

We differentiate the relative contributions of C, E, O’s by using an inverse proportional weighting system. This has been adopted in order to reflect a “least required impact” assumption. Meaning if there were 10 “O” events before a purchase transpired then we have to assume they (or at least all but the last event) are less effective than if there was only 1 “O” event and so we would assign a higher impact weight to the 1 versus the 10 events. A further approximation would also consider the likelihood of a declining marginal utility of events. A calculation example is highlighted in Table 1.

2. all events are not equal in impact

The base model assumes that C, E, O events are equal valued. Some may come to feel that a purchase offer is more powerful than a communication. This can be accommodated by assigning a differential weight to the C, E, O’s (for example O=2x, E=1.5x and C=1x) derived by some apriori judgment or by evaluating past history. Either way these adjustments can be used to help refine the weightings, a calculation example is provided in Table 2.

Where a consumer outreach event can be construed to be a combination of C, E, O’s as per the Dell example in part 1, can be accommodated by assigning multiple simultaneous scores, one for the purchase offer, another for the communication and/or experience event. The net outcome is to recognize and record the customer’s exposure to multiple behavioral impact triggers – not just one.

3. more recent events are likely (but not necessarily) more impact relevant than more distant events

A refinement for the recency/Top of Mind effect would yield a temporal distribution – in a slow-building-rapid-rise-at-the-end (asymptotic) curve. Table 3 shows the calculation using a straight-line impact assumption.

4. each event class (C, E, O) can be modelled separately

Each event class is fundamentally different from the other, consequently with data and computing sophistication it would be possible to construct individual response curves that could then be combined to the final purchase probability score.

In an idealized state it would be possible to have an advance prediction of customer or customer segment’s likelihood of a purchase. For example if the sequence of events to date yields a purchase probability of 80% then the most effective steps to close the gap and secure the purchase in the coming month would become evident from the historical database.

5. shorter sequences are likely better than longer sequences – Ockham’s razor

Weighting factors are solved by working backwards through the history involving event chains of various lengths and various components. Consequently a range of weighting values will be derived to guide future action becoming a bottom-up prescriptive tool. Moreover all inputs – with the exception of store visits/in-store experience are reasonably available with existing data trails allowing for the calculation of ROI’s, enabling the enterprise to become more knowledgeable in the cost/benefit tradeoffs of the purchase chains. The more basic versions will yield basic approximations – but also build a case for additional resources to implement a more fully engaged model for the brand.

Media Planning Utility:

Let’s get back to the model’s utility in the media world. As stated earlier, the Marketing Contact Audit model is a first generational attempt to optimize the communication across various touch points in support of the brand selling point – and ultimately to stimulate a purchase. Another conceptual model (Transmedia Planning) has recently emerged from Faris “Transmedia Planning & Brand Communities” which seeks to promote the use of different channels to communicate different parts/aspects of the brand story much like an orchestra or chorus. A variant of this idea has also been brought forward by Jeff Swystun who suggests that consistency of purpose and not brand consistency is the goal of marketers.

This model structure reinforces both of these notions and takes it a step further by coming to terms with the fundamental types of communication/language that different consumers will want to (and/or be more receptive to) have with the brand. That multiple types of behavior tasks may be required to reach brand reinforcing purchase tipping points and that the brand’s communication program will be stronger if it reflects all of these touch points. It recognizes that branding communication by itself will in time be correlated with a purchase – but the profitability of such an approach might preclude its adoption. It comes to recognize that the business of brands is the ultimate goal.

The Future

In their book Return on Customer, Peppers and Rogers talked about the customer being the most valuable asset of a company. Of nurturing that relationship and not diluting it with activities that may in fact erode the customer relationship and with it the ability of the enterprise to continue to generate a profit stream. Of striving to achieve a balance between the long term and short term needs of the customer and enterprise, of organic growth and acquisition.

This tool strives to help marketers come closer to achieving that. While it enables the calculation of purchase chain ROI’s – this is only the beginning. The true benefit comes from becoming more effective in the market place. It supplants media neutral planning with the broader end-to-end scope of behavior impact task planning.

This tool will help marketers to identify the kind of relationship their (WMHL) customers are seeking from the brand, align the brand value chain to deliver against that requirement and communicate to the customers in the same ‘language’. The opportunity is for marketers to have their customers understand, experience and reinforce the brand promise and deliver the relevance that increase the customer’s receptiveness to brand purchase offers and of course have an ROI to substantiate the investment.

This is in fact the beginning, not the end. What started as a simple question has led us to this point – at the entrance to a new path that will carve its way through the online/offline, long-tail/long-neck world where customers dictate their terms, where voices amplify at the speed of light, where everything is more important and seemingly just at the other side of the edge.

I look forward to your thoughts.

Miro

TABLE 1:

An example: 10C+3E+2O sums to 15 events in a Purchase Chain

Event type		Inverse proportional calculation	Inverse proportional weighting
C	10 events	15/10=1.5	1.5/14=10.7%
E	3 events	15/3=5	5/14=35.7%
O	2 events	15/2=7.5	7.5/14=53.6%
	15 events	14	100%

Then

10.7%C+35.7%E+53.6%O= Purchase

where:

• the purchase offers accounted for 54%

• the experience events accounted for 36%

• the contact events accounted for 11%

of the total event importance in triggering the sale

Note: the implicit assumption is that C, E and O are equal in impact effectiveness

Additional variables would be inserted into the equation as appropriate

Example: 10.7%C = xCa+yCb+zCc ; Hence if Ca=6 + Cb=1 + Cc=3 = 10, then proportional weighting yields

x=11.1% y= 66.7% z=22.2%

The extended formula:

107(.111Ca+.667Cb+.222Cc) + .357E+.536O = Purchase

TABLE 2:
Event Type	Unweighted event distribution	Inverse Proportional Weight	Weighted* event distribution	Adjusted Inverse Proportional Weight
C	10	10.7%	10 x 1= 10	17.4%
E	3	35.7%	3 x 1.5= 4.5	38.8%
O	2	53.6%	2 x 2= 4	43.7%
	15	100.0	18.5	100.0

Appendix A

Media Neutral Planning:

The Marketing Contact Audit (MCA)* model was introduced March 2005, heralding the formal genesis of media neutral planning. Its transformational importance lay in the fact that it was the first media planning tool to focus on marketing results (outputs) instead of inputs. (awareness, GRP, Share of Voice, CPM etc.) With its introduction marketers/agencies finally had a tool that allowed for better planning of advertising expenditures to help secure the greatest return on investment.

The MCA was “developed to empower brand owners/marketers to:

1) identify and select the critical contacts that are relevant for a particular brand

2) integrate across these key contact points, and

3) deliver brand experience through a relevant and pertinent set of consumer brand encounters, at a minimal cost , but with maximal impact.”*

The channel touch point’s efficacy was measured in three dimensions (rational, emotional and credible):

1) RATIONAL: “expertise is conceptualized as a contact’s ability to convey relevant information, referred to as information value hereafter”

2) EMOTIONAL: “attractiveness is conceptualized as the contact’s ability to portray the brand in emotionally attractive or appealing way, referred to as attractiveness value.”

3) CREDIBLE: “honesty, is conceptualized as the ability of a contact to influence purchase decisions through message acceptance, referred to as power.”*

and combined to form a single Contact Clout Factor metric.

Brands themselves were not assessed against these dimensions; rather their perceived share of voice in the particular channel was determined.

“The brand-contact association measures the degree to which a particular contact is associated with a particular brand within the category. Thus it is a measure of the consumer’s perception or memory of having encountered a specific brand via a particular contact.”*

Critics of the MCA model have pointed out that it does not allow for cumulative and/or cross channel media impact assessments which play a role in helping the customer reach the tipping point to buy. That the model is based on delivering a single message across touch points versus different parts of the brand story across various media to deliver a multi-dimensional message. Nor has there been any attempt to link the consumer brand characteristic to the message dimension. Since then other proprietary models have been developed by various media agencies to refine the media neutral planning process but are unavailable to the author.

*http://www.accessmylibrary.com/coms2/summary_0286-11586888_ITM