You're faced with conflicting data points in product marketing. How do you choose the right strategic path?

Sometimes patience is required. There are often stakeholders calling for answers now, but small data samples cannot produce accurate or useful hypotheses. This is especially true in the case of startups or small growing businesses. If you can network with other business owners in different markets that are similarly situated but not directly competing, you may be able to get more data and share ideas to help each other.

From my personal experience, data analysis can be quite tricky if the right data are not utilized properly or if they weren’t that right from the start. Several times during my career I have seen marketing plans with several conflicting data points that my team and me had to go deeper on the analysis to understand why the data are conflicting and there are several reasons. 1) some seasonal effects we didn’t consider either from time period point of view or from a specific region point of view where for example sales drop in several regions and grow exponentially in one of them so trend is conflicting Also the assumptions used when doing data analysis are very critical and has to be verified by further research to avoid wrong assumptions

When navigating conflicting data: ? Cross-verify data sources for accuracy ? Segment data to identify patterns or anomalies ? Conduct additional qualitative research ? Consult with cross-functional teams for insights ? Run small-scale tests to validate hypotheses DO's and DON'Ts ? Don't cherry-pick data to support preconceptions ? Do consider the context behind each data point ? Don't rush to conclusions without thorough analysis ? Do use statistical methods to determine significance ? Don't ignore outliers; investigate their causes You'll identify key discrepancies within days. You'll develop competing hypotheses in a week. Remember: In conflicting data scenarios, the goal is informed decision-making, not perfect certainty.

In my experience the differences in data come from different agendas, for example third parties may want to protect their business and may inflate or provide incomplete data therefore it is important to use different independent sources to verify like agencies or own teams to generate data.

If you didn't build and maintain the hygiene on a data source, assume that you need to double click into the data foundations. That may be easier said than done when you get into large, scaled operations but here are a few things I look at when I evaluate a data source: (1) Core use case: What was the original question this data was pulled to respond to? This should provide broad context (2) Filters: What data was excluded to provide this view? Do you have control in adding back in data to see the fuller picture or adjust inclusions? (3) Comparison/ sanity check: Do you have adjacent/correlate data that can help you investigate the validity of data that feels off?

I’ve found it important to consider your channels. In our industry and particular business we have several. We are generally a wholesale provider with resellers, but we also have a direct sales retail site. Our messaging must be different depending on if we are targeting a reseller or a retail (end-user) audience. They are motivated in different ways and need different approaches. Our retail sector also has more than one “type”. Including the experts in our industry, the novices, small businesses, and enterprises. We must know those types and develop our messaging around their particular knowledge level and motivations.

There's always more to numbers than meets the eye. If the inputs are correct, these numbers always give an accurate picture. The primary input, in this case, is your customer. Understanding your customers is priority one, and this is also where most mistakes happen. You make a mistake and then choose the wrong parameter to calculate your goal. Talking numbers, take the retention metric and use case frequency, for instance. Many brands, like Homejoy and Fab, showed tremendous growth initially but fell badly because they didn't know their customers well and chose parameters incorrectly to assess their goals.

I like to read a few industry specific newsletters regularly and the Wall Street Journal daily (at least skim through it - any good business daily will suffice). The idea is to be on the lookout and to stay abreast of current trends.